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At least 109 records · Page 6

Empirical Analysis of the Variability of Wind Generation in India: Implications for Grid Integration

We analyze variability in load and wind generation in India to assess its implications for grid integration of large scale wind projects using actual wind generation and load data from two states in India, Karnataka and Tamil Nadu. We compare the largest variations in load and net load (load -wind, i.e., load after integrating wind) that the generation fleet has to meet. In Tamil Nadu, where wind capacity is about 53% of the peak demand, we find that the additional variation added due to wind over the current variation in load is modest; if wind penetration reaches 15% and 30% by energy, the additional hourly variation is less than 0.5% and 4.5% of the peak demand respectively for 99percent of the time. For wind penetration of 15% by energy, Tamil Nadu system is found to be capable of meeting the additional ramping requirement for 98.8percent of the time. Potential higher uncertainty in net load compared to load is found to have limited impact on ramping capability requirements of the system if coal plants can me ramped down to 50percent of their capacity. Load and wind aggregation in Tamil Nadu and Karnataka is found to lower the variation by at least 20% indicating the benefits geographic diversification. These findings suggest modest additional flexible capacity requirements and costs for absorbing variation in wind power and indicate that the potential capacity support (if wind does not generate enough during peak periods) may be the issue that has more bearing on the economics of integrating wind

17 WIND ENERGY↗

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. 1 -- National Study, Executive Summary

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Greening the Grid: Advances in Production Cost Modeling for India Renewable Energy Grid Integration Study

The Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid study uses advanced weather and power system modeling to explore the operational impacts of meeting India's 2022 renewable energy targets and identify actions that may be favorable for integrating high levels of renewable energy into the Indian grid. The study relies primarily on a production cost model that simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. This fact sheet provides a detailed look at each of these models, including their common assumptions and the insights provided by each.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Timing the Flames: Geostationary Satellite Detection of Diurnally Shifting Stubble Burning in Northwestern India

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts.

post-monsoon stubble burning; northwestern India;↗

India RE Grid Integration Study

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established a target of 175 gigawatts (GW) of installed RE capacity by 2022, including 60 GW of wind and 100 GW of solar, up from 29 GW wind and 9 GW solar at the beginning of 2017. Thanks to advanced weather and power system modeling made for this project, the study team is able to explore operational impacts of meeting India's RE targets and identify actions that may be favorable for integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Western Region

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: -To better anticipate, understand, and mitigate system constraints that could affect RE integration; and - To provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Greening the Grid: Integrating 175 Gigawatts of Renewable Energy into India's Electric Grid - A Detailed Look at the Southern Region

The higher-spatial-resolution model of 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. II - Regional Study' (the Regional Study), which better represents the impact of congestion on least-cost scheduling and dispatch, provides a deeper understanding of the relationship among renewable energy (RE) location, transmission, and system flexibility with regard to RE integration, compared to 'Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid, Vol. I - National Study.' The Regional Study validates the relative value of mitigation strategies demonstrated in the National Study - namely, coordinated operations among states reduce production costs, and reducing coal minimum generation levels reduces RE curtailment. Significantly, the Regional Study also highlights a potential barrier to realizing the value of these mitigation strategies: when locations of RE development are planned independently of state-level transmission, intrastate congestion can result in undesirable levels of RE curtailment. Therefore a key objective of this study is to illustrate to state-level power system planners and operators, in particular, how a higher-resolution model, inclusive of intrastate granularity, can be used as a planning tool for two primary purposes: to better anticipate, understand, and mitigate system constraints that could affect RE integration; and to provide a modeling framework that can be used as part of future transmission studies and planning efforts. The Regional Study is not intended to predict precisely how RE will affect state-level operations. There is considerable uncertainty regarding the locations of the RE development, as well as how contract terms can affect access to the inherent physical flexibility of the system. But the scenarios analyzed identify the types of issues that can arise under various RE and transmission expansion pathways. The model developed for this study provides a rigorous framework for future work and can be updated with the characteristics of new capacity as more information on the future power system is known.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Framework for Evaluating Grid Readiness for Integrating Electric Vehicles and Utility Scale Storage in India

Electric vehicles (EVs) and distributed solar are poised to grow substantially in India in the coming years following ambitious Government of India targets. The localized impact of these changes, both in terms of infrastructure investments and demand patterns, are not well understood, nor are tools for this type of analysis readily available. This paper describes the development of a framework that can analyze network readiness in terms of feeder impacts for distributed energy resources (DERs) including growing EV penetration, and the potential solutions introduced by utility-scale battery energy storage systems (BESSs). The building blocks of the feeder analysis require multiple data sets to be compiled into a usable network model. The work is driven by feeder head and distribution transformer (DT) loading data along with all the technical specifications and schematics of distribution feeders. These measured data sets are conditioned to remove any afflictions, and the cleaned load profiles are used to perform multi-year quasi-static time-series power flow analyses on detailed three-phase feeder models. EVs translated to grid-tied loads are represented with aggregated EV demand profile estimates based on possible charging scenarios in residential sector, and in workplace and/or public charging stations. Finally, BESSs are evaluated for their cost-effectiveness in the framework through an initial screening that includes the benefits of grid service applications to mitigate present and future overloading scenarios. The outcomes from this framework are expected to help utilities gauge the readiness of their distribution grid for integrating an increasing number of EVs as well as load growth during a projected multi-year time horizon, where BESSs can contribute in making the grid more reliable.

electric vehicles↗

Estimating Trends and Variation of Net Biome Productivity in India for 1980–2012 Using a Land Surface Model

In this paper we explore the trend in net biome productivity (NBP) over India for the period 1980–2012 and quantify the impact of different environmental factors, including atmospheric CO 2 concentrations ([CO 2 ]), land use and land cover change, climate, and nitrogen deposition on carbon fluxes using a land surface model, Integrated Science Assessment Model. Results show that terrestrial ecosystems of India have been a carbon sink for this period. Driven by a strong CO 2 fertilization effect, magnitude of NBP increased from 27.17 TgC/yr in the 1980s to 34.39 TgC/yr in the 1990s but decreased to 23.70 TgC/yr in the 2000s due to change in climate. Adoption of forest conservation, management, and reforestation policies in the past decade has promoted carbon sequestration in the ecosystems, but this effect has been offset by loss of carbon from ecosystems due to rising temperatures and decrease in precipitation.

54 ENVIRONMENTAL SCIENCES↗

Black carbon-climate interactions regulate dust burdens over India revealed during COVID-19

India as a hotspot for air pollution has heavy black carbon (BC) and dust (DU) loadings. BC has been identified to significantly impact the Indian climate. However, whether BC-climate interactions regulate Indian DU during the premonsoon season is unclear. Here, using long-term Reanalysis data, we show that Indian DU is positively correlated to northern Indian BC while negatively correlated to southern Indian BC. We further identify the mechanism of BC-dust-climate interactions revealed during COVID-19. BC reduction in northern India due to lockdown decreases solar heating in the atmosphere and increases surface albedo of the Tibetan Plateau (TP), inducing a descending atmospheric motion. Colder air from the TP together with warmer southern Indian air heated by biomass burning BC results in easterly wind anomalies, which reduces dust transport from the Middle East and Sahara and local dust emissions. The premonsoon aerosol-climate interactions delay the outbreak of the subsequent Indian summer monsoon.

54 ENVIRONMENTAL SCIENCES↗

Rapidly expanding nuclear arsenals in Pakistan and India portend regional and global catastrophe

Pakistan and India may have 400 to 500 nuclear weapons by 2025 with yields from tested 12- to 45-kt values to a few hundred kilotons. If India uses 100 strategic weapons to attack urban centers and Pakistan uses 150, fatalities could reach 50 to 125 million people, and nuclear-ignited fires could release 16 to 36 Tg of black carbon in smoke, depending on yield. The smoke will rise into the upper troposphere, be self-lofted into the stratosphere, and spread globally within weeks. Surface sunlight will decline by 20 to 35%, cooling the global surface by 2° to 5°C and reducing precipitation by 15 to 30%, with larger regional impacts. Recovery takes more than 10 years. Net primary productivity declines 15 to 30% on land and 5 to 15% in oceans threatening mass starvation and additional worldwide collateral fatalities.

54 ENVIRONMENTAL SCIENCES↗

Data Center Energy Efficiency Standards in India: Preliminary Findings from Global Practices

Global data center energy consumption is growing rapidly. In India, information technology industry growth, fossil-fuel generation, and rising energy prices add significant operational costs and carbon emissions from energy-intensive data centers. Adoption of energy-efficient practices can improve the global competitiveness and sustainability of data centers in India. Previous studies have concluded that advancement of energy efficiency standards through policy and regulatory mechanisms is the fastest path to accelerate the adoption of energy-efficient practices in the Indian data centers. In this study, we reviewed data center energy efficiency practices in the United States, Europe, and Asia. Using evaluation metrics, we identified an initial set of energy efficiency standards applicable to the Indian context using the existing policy mechanisms. These preliminary findings support next steps to recommend energy efficiency standards and inform policy makers on strategies to adopt energy-efficient technologies and practices in Indian data centers.

Raje, Sanyukta↗

Machine Learning Application to Assess Occurrence and Saturations of Methane Hydrate in Marine Deposits Offshore India

Artificial Neural Networks (ANN) were used to assess methane hydrate occurrence and saturation in marine sediments offshore India. The ANN analysis classifies the gas hydrate occurrence into three types: methane hydrate in pore space, methane hydrate in fractures, or no methane hydrate. Further, predicted saturation characterizes the volume of gas hydrate with respect to the available void volume. Log data collected at six wells, which were drilled during the India National Gas Hydrate Program Expedition 02 (NGHP-02), provided a combination of well log measurements that were used as input for machine learning (ML) models. Well log measurements included density, porosity, electrical resistivity, natural gamma radiation, and acoustic wave velocity. Combinations of well logs used in the ML models provide good overall balanced accuracy (0.79 to 0.86) for the prediction of the gas hydrate occurrence and good accuracy (0.68 to 0.92) for methane hydrate saturation prediction in the marine accumulations against reference data. The accuracy scores indicate that the ML models can successfully predict reservoir characteristics for marine methane hydrate deposits. In conclusion, the results indicate that the ML models can either augment physics-driven methods for assessing the occurrence and saturation of methane hydrate deposits or serve as an independent predictive tool for those characteristics.

58 GEOSCIENCES↗

Wind Resource Assessment of Gujarat (India)

India is one of the largest wind energy markets in the world. In 1986 Gujarat was the first Indian state to install a wind power project. In February 2013, the installed wind capacity in Gujarat was 3,093 MW. Due to the uncertainty around existing wind energy assessments in India, this analysis uses the Weather Research and Forecasting (WRF) model to simulate the wind at current hub heights for one year to provide more precise estimates of wind resources in Gujarat. The WRF model allows for accurate simulations of winds near the surface and at heights important for wind energy purposes. While previous resource assessments published wind power density, we focus on average wind speeds, which can be converted to wind power densities by the user with methods of their choice. The wind resource estimates in this study show regions with average annual wind speeds of more than 8 m/s.

17 WIND ENERGY↗

Accelerating Improvements in the Energy Efficiency of Room Air Conditioners (RACs) in India: Potential, Cost-Benefit, and Policies (Interim Assessment)

Falling AC prices, increasing incomes, increasing urbanization, and high cooling requirements due to hot climate are all driving increasing uptake of Room Air Conditioners (RACs) in the Indian market. Air conditioning already comprises 40-60% of summer peak load in large metropolitan Indian cities such as Delhi and is likely to contribute 150 GW to the peak demand in 2030. Standards and labeling policies have contributed to improving the efficiency of RACs in India by about 2.5% in the last 10 years (2.5% per year) while inflation adjusted RAC prices have continued to decline. In this paper, we assess the technical feasibility, cost-benefit, and required policy enhancements by further accelerating the efficiency improvement of RACs in India. We find that there are examples of significantly more accelerated improvements such as those in Japan and Korea where AC efficiency improved by more than 7% per year resulting in almost a doubling of energy efficiency in 7 to 10 years while inflation adjusted AC prices continued to decline. We find that the most efficient RAC sold on the Indian market is almost twice as efficient as the typical AC sold on the market and hence see no technology constraints in a similar acceleration of improvement of efficiency. If starting 2018, AC efficiency improves at a rate of 6% instead of 3%, 40-60 GW of peak load (equivalent to connected load of 5-6 billion LED bulbs), and over 75 TWh/yr (equivalent to 60 million consumers consuming 100 kWh/month) will be saved by 2030; total peak load reduction would be as high as 50 GW. The net present value (NPV) of the consumer benefit between 2018-2030 will range from Rs 18,000 Cr in the most conservative case (in which prices don’t continue to decline and increase based estimates of today’s cost of efficiency improvement) to 140,000 Cr in a more realistic case (in which prices are not affected by accelerated efficiency improvement as shown by historical experience). This benefit is achievable by ratcheting up the 1 star level for fixed and inverter ACs to the level of today’s five star rating for inverter ACs by 2022. Bulk procurement (similar to the Domestic Efficient Lighting Program) and incentive programs can complement the accelerated ratcheting up of star levels. Similar programs can also be implemented for other types of ACs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Establishing a commercial building energy data framework for India

Buildings account for over 40% of the world’s energy consumption and are therefore a key contributor to a country’s energy as well as carbon budget. Understanding how buildings use energy is critical to understanding how related policies may impact energy use. Data enables decision making, and good quality data arms consumers with the tools to compare their energy performance to their peers, allowing them to differentiate their buildings in the real estate market on the basis of their energy footprint. Good quality data are also essential for policy makers to prioritize their energy saving strategies and track implementation. The United States’ Commercial Building Energy Consumption Survey (CBECS) is an example of a successful data framework that is highly useful for governmental and nongovernmental initiatives related to benchmarking energy forecasting, rating systems and metrics, and more. The Bureau of Energy Efficiency (BEE) in India developed the Energy Conservation Building Code (ECBC) and launched the Star Labeling program for a few energy-intensive building segments as a significant first step. However, a data driven policy framework for systematically targeting energy efficiency in both new construction and existing buildings has largely been missing. There is no quantifiable mechanism currently in place to track the impact of code adoption through regular reporting/survey of energy consumption in the commercial building stock. In this paper we present findings from our study that explored use cases and approaches for establishing a commercial buildings data framework for India.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Case for All New City Buses in India to be Electric

Indian cities are struggling to keep the air breathable for inhabitants, due in part to emissions from diesel buses. While the case for electric buses, and more generally, zero emission buses, has always been clear from an urban air pollution perspective, the economic case depended strongly on their environmental benefits. However, the situation seems different today. We illustrate that when the benefits of recent dramatic declines in Lithium battery prices are fully realized, the total cost of ownership of urban (intra-city) electric buses is lower than that for diesel buses in India even without subsidies. Factoring in the air quality benefits, projected reductions in the cost of batteries and solar electricity, it becomes evident that transitioning to an all-electric bus fleet presents an enormous opportunity for India to reduce urban air pollution while improving the finances of urban bus transit agencies. The policy ecosystem that delivered substantial price reductions and large-scale rapid deployment of solar PV and LEDs is a model to achieve similar outcomes for battery electric buses. Well-designed high volume auctions and clear long term ambitious targets for fleet electrification could achieve to rapid electrification with little net public subsidy in the long-run.

33 ADVANCED PROPULSION SYSTEMS↗