Ministry of New and Renewable Energy

Abstract Details of methane sorption properties of some Indian coals ranging in rank from high-volatile bituminous C (0.62% Ro max) to medium-volatile bituminous coal (1.46% Ro max) were investigated to determine the major factors influencing gas adsorption capacity and desorption rate. Variables studied included moisture content, mineral-matter content, rank, and coal type (maceral composition). Adsorption isotherm analysis of dry coals showed that adsorption capacity followed a second-order polynomial trend with rank. Equilibrium moist samples showed a linear increase in adsorption capacity with rank and had a significantly reduced adsorption capacity compared to the dry coals, with the reduction being related to the moisture content. Mineral matter acted as a simple diluent to the gas adsorption capacity of the coals and was found to be nonadsorbent. Adsorption capacity (moist) was reduced by 0.32 cm3/g (10 ft3 gas/t) for every 1% increase in the ash yield. Bright and dull coal lithotypes showed strong separation in their adsorption capacities on an as analyzed basis, with the bright coals adsorbing greater quantities of gas. On a dmmf basis, however, no relationship was observed between coal type and gas storage capacity. Comparison of maceral composition with adsorption capacity (dry) confirmed this observation. Effective diffusivity (De) of methane through the coal was seen to be affected by coal type and rank. Effective diffusivity, De, decreased as rank increased, which is related to the increasing microporous nature of the coal. Bulk coals tested had 2-3 times larger effective diffusivities than bright coals, and dull coals had intermediate rates. The larger De values for the bulk coals may be related to the presence of collodetrinite coupled with mineral matter, which acts as higher permeability pathways for the gas compared with the high-ash dull coals dominated by inertinite macerals. Differences were noted with similar-age (Permian) Australian coals, where methane adsorption capacities were larger and coal type had a stronger influence on adsorption capacity.

This paper presents the analysis of visual degradation data collected during an All-India Survey of Photovoltaic Module Degradation conducted in 2013, in which 57 crystalline silicon modules were inspected in the five different climatic zones of India. Analysis of the data indicates that the highest percentage of modules suffered discoloration in the Hot and Dry climatic zone, with the Hot and Humid zone coming in second in the list. A higher percentage of modules have suffered corrosion in the Hot and Humid zone, as compared with other zones. The modules installed in the Cold climate suffered the least degradation. Both discoloration and corrosion have been seen in modules across all age groups, even in some of the modules installed less than five years ago. On the other hand, delamination and backsheet degradation have been seen only in modules more than a decade old. The visual degradation data have been correlated with the electrical performance data and reaffirm the direct relation between encapsulant discoloration and reduction in short-circuit current and output power, as well as that of series resistance with metal corrosion.

Abstract The All India Survey of Photovoltaic Module Reliability 2014 is an enhanced version of the survey conducted in the previous year, with detailed characterization of PV modules including current‐voltage, infrared and electroluminescence imaging, visual inspection, insulation resistance test and interconnect breakage test. More than a thousand modules were inspected in the field and the main results of the survey are presented in this paper. The average P max degradation rate for the so‐called ‘good’ modules (Group X) is 1.33%/year which is higher than that commonly projected by manufacturers, and widely employed in financial calculations. Modules falling in the ‘not‐so‐good’ category (Group Y) show even higher degradation rates, and it is at least partly due to higher number of micro‐cracks in the modules, and increased degradation of the packaging materials like encapsulant, backsheet, etc. Modules in ‘Hot’ climates degrade faster than modules in the ‘Non‐Hot’ climates. Degradation in fill factor is the primary cause for performance degradation in the young modules (ages <5 years), whereas short‐circuit current degradation is the main contributor to power degradation in the older modules. Small installations (<100 kW p capacity) show higher degradation than large systems, which may be partly due to lack of proper due diligence by the owner at the time of procurement and installation.

This communication presents the comparative experimental study based on energy and exergy analyses of a typical solar air heater collector with and without temporary heat energy storage (THES) material, viz. paraffin wax and hytherm oil. Based on the experimental observations, the first law and the second law efficiencies have been calculated with respect to the available solar radiation for three different arrangements, viz. one arrangement without heat storage material and two arrangements with THES, viz. hytherm oil and paraffin wax, respectively. It is found that both the efficiencies in case of heat storage material/fluid are significantly higher than that of without THES, besides both the efficiencies in case of paraffin wax are slightly higher than that of hytherm oil case. Copyright © 2011 John Wiley & Sons, Ltd.

The alleged reliability has led the longest warranty period for Photovoltaic (PV) modules up to 20–25 years; it becomes possible after understanding the failure mode and degradation analysis of PV module. Failure mode decreases the performance of the PV module throughout the long-term outdoor exposure. The main objective of the present study is to identify the failure mechanism and failure mode of solar PV modules and their impact on degradation in operating conditions. Assessment of previous studies on rate indicates the highest performance losses at initial stage of outdoor exposure and a degradation drop-off of 0.014% per year. In this context, risk priority number (RPN) analysis is carried out to identify the severity of the failure mode, which affect the system performance for c-Si technologies. However, hot spot and de-lamination are degradation modes related to safety issue with lower value of RPN <50.

Life cycle metrics evolution specific to the climate zone of photovoltaic (PV) operation would give detailed insights on the environmental and economic performance. At present, vast literature is available on the PV life cycle metrics where only the output energies ignoring the degradation rate (DR) influence. In this study, the environ-economic analysis of three PV technologies, namely, multi-crystalline silicon (mc-Si), amorphous silicon (a-Si) and hetero-junction with an intrinsic thin layer (HIT) have been carried out in identical environmental conditions. The energy performance parameters and the DR rate of three PV technologies are evaluated based on the monitored real time data from the installation site in hot semi-arid climates. The assessment demonstrates that the HIT PV module technology exhibits more suitable results compared to mc-Si and a-Si PV systems in hot semi-arid climatic conditions of India. Moreover, energy metrices which includes energy payback time (EPBT), energy production factor (EPF) and life cycle conversion efficiency (LCCE) of the HIT technologies are found to be 1.0, 24.93 and 0.15 years, respectively. HIT PV system has higher potential to mitigate the CO2 and carbon credit earned compared to mc-Si and a-Si PV system under hot semi-arid climate. However, the annualized uniform cost (UAC) for mc-Si (3.60 Rs/kWh) and a-Si (3.40 Rs/kWh) are more admissible in relation to the HIT (6.63 Rs/kWh) PV module type. We conclude that the approach of considering DR influenced life cycle metrics over the traditional approach can support to identify suitable locations for specific PV technology.

The accuracy of outdoor performance of a photovoltaic (PV) array can be improved by considering the spectral effects. In this paper, the impact of seasonal spectral variations on the three different silicon PV technologies: single junction amorphous silicon (a-Si), Hetero-junction with Intrinsic Thin-layer (HIT) and multi crystalline silicon (mc-Si) has been presented first time in Indian environmental conditions. The spectral effect on HIT PV module technology has been presented first time along with the first simultaneous study of variation in spectral indicators by useful fraction (UF), average photon energy (APE) and spectral mismatch factor (MMF), based on monthly and seasonal data. The maximum observed variation in UF was 26.4, 8.2, 10.8 %, while in MMF, variation was up to 24.7, 7.6, 8.2 % for a-Si, HIT and mc-Si, respectively, and in APE variation was up to 15.3 %. Among all three technology modules, first time reported HIT technology showed the least variation while maximum variation was observed in a-Si technology. The observed spectral effect variations have been discussed on Performance Ratio and compared with reported results of other global sites. The value and trends of spectral parameters are important to understand the effect of spectral variation on different technology. This study is especially important in Indian subcontinent perspective because of the strong monsoon season, where observed variation in the spectrum-related parameter found to be highest among all the seasons.

Capacity-building is acknowledged as an essential requirement for addressing environmental and developmental challenges in developing countries. In particular, the capacity to manage technological change is an important prerequisite for climate change mitigation, adaptation and green growth. Despite the importance of such capacity, there are surprisingly few empirical accounts unpacking its different dimensions and exploring how it might be built in developing countries in the context of climate and sustainable development challenges. In this paper, we contribute to this sparse literature through an in-depth qualitative case study on energy efficiency in India. Specifically, we take a systemic and evolutionary perspective to investigate how the Bureau of Energy Efficiency developed and implemented its programs to promote energy efficiency in household appliances, light-emitting-diode lamps and energy-intensive industries – and how in doing so, both drew upon existing capacity within and outside the country, and also built new capacity, to achieve significant energy savings.Key policy insights Since the capacity to manage technological change is distributed among a range of actors, policymakers require the ability to understand capacity needs from multiple actors’ perspectives.Policymakers need to respond to evolving capacity needs over the course of a program – from strategic program design, trust-building and resource mobilization in early stages, to administration in later stages.‘System operators/integrators’ can play a crucial role during the early stages of a program by helping develop capacity and sustaining it by creating a demand for such capacity, as well as bringing together actors, enabling coordination, and building coalitions among them.Preliminary analysis suggests that the Bureau of Energy Efficiency programs investigated in this paper resulted in significant energy savings and CO2 emission reductions.

The analysis of performance degradation in photovoltaic (PV) modules with c-Si technologies as observed in the All-India Survey of PV Module Reliability 2018 is presented in this article. The degradation rates are correlated with the module age, system size, mounting configuration, and climate of deployment. Key failure modes responsible for the higher degradation rates seen in certain sites are identified using visual, infrared, and electroluminescence imaging. Potential-induced degradation is found to be the key mechanism responsible for higher degradation rates seen in Young sites. Also, deployment in hot climates and rooftops is seen to accelerate degradation. Multipoint analysis of degradation rates is presented at sites inspected in prior All-India Surveys.

A survey of field-aged crystalline silicon modules in various climatic conditions in India was carried out, focusing on modules, which show visible signs of degradation. Analysis of the survey data indicates that the power degradation rate is highest in the Hot & Dry climatic zone, followed by the Hot & Humid zone, while it is least in the Cold zone. The degradation in power output of crystalline silicon modules is primarily due to reduction in the short-circuit current, followed by decrease in fill factor while the decrease in open-circuit voltage is very small. Analysis of the survey data also indicates that degradation rate of multi-crystalline silicon is slightly higher than that of mono crystalline silicon.

Microdroplet chemistry is now well-known to be able to remarkably accelerate otherwise slow reactions and trigger otherwise impossible reactions. The uniqueness of the microdroplet is attributable to either the air-water interface or solid-liquid interface, depending on the medium that the microdroplet is in contact with. To date, the importance of the solid-liquid interface might have been confirmed, but the contribution from the air-water interface seems to be elusive due to the lack of method for generating contactless microdroplets. In this study, we used a droplet atomization method with acoustic levitation. Upon manipulation of the acoustic field, the levitated parent droplet can be further atomized into progeny microdroplets. With this method, only the air-water interface was present, and a large variety of reactions were successfully tested. We anticipate that this study can be an advance toward the understanding of the air-water interfacial processes of microdroplet chemistry.

This paper presents the energy and exergy performance evaluation of heterojunction with intrinsic thin layer (HIT) solar photovoltaic (SPV) module for a particular day of different months of the year of a typical climatic zone of north India. The energy, exergy and power conversion efficiencies have been calculated and plotted against time based on hourly insolation. The variation in all the efficiencies has been observed with respect to variation in solar radiation and wind speed and found that all the efficiencies are higher in morning and evening time as compared to noon time which is due to the variation in temperature of module throughout the day. Performance of SPV module has been found to be the best in the month of February i.e. all the three efficiencies have been found to be the highest among all the months analysed and presented in the study for the month of February. The energy efficiency is found to be always higher than that power conversion and exergy efficiencies. However, exergy efficiency in some months like February, May, June, September, October and December has been found to be higher than that of power conversion efficiency, reverse is found in rest of the months.

OBJECTIVES: Persons with injection drug use (IDU) have high healthcare utilization. Consequently, healthcare providers have opportunities to identify and treat underlying substance use disorders (SUD) that drive these hospitalizations. The study purpose was to characterize current SUD evaluation and treatment practices by primary and consulting services during hospitalization for severe infections related to IDU. METHODS: This study is a retrospective chart review of inpatient admissions to an academic medical center. The 2 inclusion criteria were documentation of IDU in clinical notes and the presence of an infection likely related to IDU. Demographic and clinical data were extracted from electronic medical records. RESULTS: A total of 108 inpatient admissions met inclusion criteria and were included in the study. The most common infections related to IDU were endocarditis (n = 65, 60.2%) and osteomyelitis (n = 27, 25.0%). The primary team explicitly documented substance use in the H&P and progress notes in 103 (95.4%) hospitalizations and in 84 (77.8%) at discharge. Opioid use disorder was coded by International Classification of Diseases, Ninth Revision in 62 (57.4%). The most frequent intervention was screening, brief intervention, and referral to treatment in 99 (91.7%) episodes. The vast majority of patients did not have specific plans or recommendations for SUD treatment upon discharge. CONCLUSIONS: Though more than half of the patients in this study had opioid use disorder, pharmacotherapy for opioid use disorder was typically not provided, and screening, brief intervention, and referral to treatment (SBIRT) was the most common intervention. There are significant gaps in the clinical assessment, diagnosis, and management of SUD in persons hospitalized with life-threatening complications of IDU, leaving many opportunities to improve care for this complex patient population.

The paper presents a fast and efficient method for the detection and characterisation of delamination in photovoltaic (PV) modules by using active infrared thermography approach. A discrete part of PV module was irradiated by step heating and its thermal image sequence was used to detect and analyse delamination. Different types of heating source for thermal excitation for this application have been studied. An electro-thermal model was developed to simulate the active thermography approach for the characterisation of delamination in PV module by equivalent resistance-capacitance (RC) network using a circuit simulator. This simulation approach was used to estimate the extent of delamination in the module and to determine the optimum parameters for the characterisation of delamination. Different applications based on front and backsides of heating the module were also proposed in this paper. The proposed method has the potential to be employed for the quality check of PV modules during inline production as well as for the predictive maintenance of outdoor PV plants.

Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur due to loss of power, misalignment, failure of instruments, insufficient cleaning or other reasons. Quality check procedures identify such malfunctioning and mark untrustworthy data by flags. Even well maintained stations with good equipment usually show gaps. In the case of the Indian SRRA network with its 51 stations operating since 2011, typically around 7% of the data are flagged as potentially erroneous or missing. Duration of gaps ranges from few minutes to several days. However many applications such as solar energy performance simulations need continuous time-series. Therefore it is required to fill the measurement gaps with reasonable data. Depending on duration and type of missing parameters various procedures can be used to fill gaps. This paper describes a set of procedures called 'basic gap filling' for solar irradiance, which can be applied without having available additional data. From the over-determined set of global, diffuse and direct radiation a single missing parameter can be calculated from the other two. When two or more solar irradiance components are missing for short gaps, clearness indices are derived to calculate the missing irradiance components. Basic gap filling procedure is applied as part of the SRRA/SolMap projects. The accuracy of the applied basic gap filling methodology is tested and the results show a mean bias of ca. 3 % over GHI, DNI and DHI over all types of gaps.

World's largest DNI measurement network of 51 automatic meteorological stations with solar radiation instruments fulfilling the highest commercially available standards is operating in India. The Indian Ministry of New and Renewable Energy (MNRE) in 2011 started this extensive solar resource monitoring cum meteorological station network under the Solar Radiation Resource Assessment (SRRA) project. This paper highlights the overall performance of the stations over more than one year and documents the specific problems and errors observed in field operation. Following best practices quality assessment tests, a data flagging system to identify, differentiate and quantify different types of errors and other functionalities have been implemented as part of the SolMap project. The quality assessment tests check the plausibility of data, differentiate trustworthy data from likely erroneous data and flag them accordingly. The quality flag statistics of all 51 stations reveals that some stations are performing very well and others need more attention to improve. In the period from January 2012 to March 2013 on an average over all 51 stations, 92% of the solar radiation data are classified as correct. The quality control system has proven to be very effective for detecting errors in functionality of the stations. Values flagged erroneous along with missing values are considered as gaps. Many applications such as solar energy performance simulations need continuous time-series. Therefore it is required to fill the measurement gaps with reasonable data. This paper also describes a set of procedures called ‘basic gap filling’ for solar irradiance. The accuracy of the applied basic gap filling methodology is tested and the results show a mean bias of ca. 3% over GHI, DNI and DHI over all types of gaps. Automated alarms, sensor cleaning switch, bird protection cages for wind sensors etc. are some of the efforts SRRA took for smoother operation. Regular cleaning of the radiometers remains the most challenging task for the SRRA network.

Abstract Long short-term memory (LSTM) models based on specialized deep neural network-based architecture have emerged as an important model for forecasting time-series. However, the literature does not provide clear guidelines for design choices, which affect forecasting performance. Such choices include the need for pre-processing techniques such as deseasonalization, ordering of the input data, network size, batch size, and forecasting horizon. We detail this in the context of short-term forecasting of global horizontal irradiance, an accepted proxy for solar energy. Particularly, short-term forecasting is critical because the cloud conditions change at a sub-hourly having large impacts on incident solar radiation. We conduct an empirical investigation based on data from three solar stations from two climatic zones of India over two seasons. From an application perspective, it may be noted that despite the thrust given to solar energy generation in India, the literature contains few instances of robust studies across climatic zones and seasons. The model thus obtained subsequently outperformed three recent benchmark methods based on random forest, recurrent neural network, and LSTM, respectively, in terms of forecasting accuracy. Our findings underscore the importance of considering the temporal order of the data, lack of any discernible benefit from data pre-processing, the effect of making the LSTM model stateful. It is also found that the number of nodes in an LSTM network, as well as batch size, is influenced by the variability of the input data.

Abstract The present research aims to enhance heat transfer in straight and wavy profile heat sinks using the same length and hydraulic diameter with different microchannel geometries (triangular, rectangular, trapezoidal, semi-circular, and circular) for uses in electronics, inkjet printing, high heat flux cooling of lasers, and other domains. The nanofluid employed is water/aluminum oxide (water/Al 2 O 3 ), and the flow regime is laminar. The range of Reynolds number (Re) in this study was 220 ≤ Re ≤ 550, and the concentrations of nanoparticle Al 2 O 3 with Heavy Water (2H 2 O) were 1.2 % volume. This investigation uses 3-dimensional Computational Fluid Dynamics (CFD) simulation software to investigate the heat transfer characteristics of several cross-sectioned microchannels. The numerical investigation utilizes the finite volume approach, and the CFD analysis is validated with accessible literature with different wavy profiles. According to the CFD simulation results, the microchannel with a circular cross-section has the highest heat transfer performance (up to 18 %) among the other cross-sections. The circular cross-section microchannel seemed to have the most significant increase in coolant temperature (by 9–22 %). The analysis outcomes prove that the microchannel with a circular cross-section has the highest performance for heat transfer; the triangular channel has the lowest performance under the same geometric parameters and boundary conditions. So, it is suggested that a circular microchannel can be used for a heat-carrying capacity of 150 W/cm 2 , a hydraulic diameter of 500 µm, and a Reynolds number equal to 500.

A<italic>Jatropha curcas</italic>oil (JCO) based hybrid microemulsion fuel (MHBF) comprising pretreated JCO–1-butanol–ethanol preparation, characterization, engine performance, combustion and emission analysis.

• Anaerobic digester yields dynamic behavior under frequent changes in feed. • An empirical approach utilizing ANN has been used. • NARX network has been used to model the dynamic behavior. • Predictions of biogas produced compare well with plant data within ±8% deviation. In waste-to-energy plants, there is every likelihood of variations in the quantity and characteristics of the feed. Although intermediate storage tanks are used, but many times these are of inadequate capacity to dampen the variations. In such situations an anaerobic digester treating waste slurry operates under dynamic conditions. In this work a special type of dynamic Artificial Neural Network model, called Nonlinear Autoregressive Exogenous model, is used to model the dynamics of anaerobic digesters by using about one year data collected on the operating digesters. The developed model consists of two hidden layers each having 10 neurons, and uses 18 days delay. There are five neurons in input layer and one neuron in output layer for a day. Model predictions of biogas production rate are close to plant performance within ±8% deviation.