ABSTRACT
From 2018 to 2022, on average, 70% of the Brazilian effective electric generation was produced by hydropower, 10% by wind power, and 20% by thermal power plants. Over the last five years, Brazil suffered from a series of severe droughts. As a result, hydropower generation was reduced, but demand growth was also declined as results of the COVID-19 pandemic and economic recession. From 2012 to 2022, the Brazilian reservoir system operated with, on average, only 40% of the active storage, but storage recovered to normal levels in the first three months of 2022. Despite large capacity of storage reservoirs, high volatility of the marginal cost of energy was observed in recent years. In this paper, we used two optimization models, NEWAVE and HIDROTERM for our study. These two models were previously developed for mid-range planning of the operation of the Brazilian interconnected power system. We used these two models to optimize the operation and compared the results with observed operational records for the period of 2018-2022. NEWAVE is a stochastic dual dynamic programming model which aggregates the system into four subsystems and 12 equivalent reservoirs. HIDROTERM is a nonlinear programming model that considers each of the 167 individual hydropower plants of the system. The main purposes of the comparison are to assess cooperation opportunities with the use of both models and better understand the impacts of increasing uncertainties, seasonality of inflows and winds, demand forecasts, decisions about storage in reservoirs, and thermal production on energy prices. © World Environmental and Water Resources Congress 2023.All rights reserved
ABSTRACT
The COVID-19 outbreak has elicited forced lockdown conditions for all anthropogenic emissions across the globe. It has brought an opportunity for the researchers to sort out the relative contribution of the environmental pollutants which are emerged from the coal-based thermal power plants and other industrial sectors. In countries like India, some industrial sectors and thermal power plants coexist; henceforth, they mutually produce NO2 concentration canopy in the upper atmosphere in raised form. Focusing on this issue, the present work intends to explore the NO2 emission hot-spots' foci using switch-off conditions in consequence of emergency lockdown. Our results indicate that stable ( C V low and NO 2 max ) and large NO2 concentration canopy is noticeable in the inter-state border areas among Chhattisgarh, Bihar, Madhya Pradesh, and Jharkhand (around "Govind Ballabh Part Sagar" reservoir) where a cluster of thermal power plant is located. The "OFF" situation also proposes a close correspondence between the NO2 richness column and installed capacity (R 2 value > 0.7 with 0.0002 p value). States that are situated in the eastern part of the country and megacities like Delhi and Kolkata represent a crucial role in NO2 emission while in certain regions of south India are more or less safe from NO2 emission. As a consequence, the lockdown has created a temporary pollution baseline for tropospheric NO2 that offers research prospects to think of alternate sources of energy that can maintain environmental health as well as human well-being.
ABSTRACT
In the present study, the atmospheric concentrations of Carbon Monoxide (CO) over India during COVID-19 (2020) were studied by comparing it with 2019 and 2021. COVID-19 has created an undesirable impact all over the world. However, as a blessing in disguise, these measures have a positive effect on the environment due to closing the mass gathering places. The work has undergone using the TROPOMI instrument, on-board Sentinel-5 Precursor. The results, evidence that human activities like transportation in Delhi, Industrial activities near Indo-Gangetic Plain have sharply fallen during the lockdown phase. On Contrary, there is a sharp increment in the area of Thermal power plants being coal-based. On the whole, the mean concentration of CO over India has minimal change due to long lifetime (1~2 months), indicating the duration of the (68 days) lockdown did not capture prompt and short-term atmospheric change. © 2021 IEEE.
ABSTRACT
Among the G20 countries, China is the only country to experience an increase in electricity generation from coal-fired thermal power plants from 2019 to 2020. This study aims to develop an analytical framework combining metafrontier data envelopment analysis with the logarithmic mean Divisia index for a detailed decomposition analysis of ‘mass-based’ energy-related CO2 reduction potential through efficiency improvements in coal-fired thermal power plants in China. The results show that inefficiency in power generation can be largely attributed to differences in the location of power plants and the production scale. Moreover, the impact of regional heterogeneity on the changes in power generation efficiency is more notable for the small–medium power plants in the northeast region than the large power plants in the western region in China. However, when focusing on the mass-based CO2 reduction potential associated with the regional heterogeneity, its positive effects in the western region for the large power plants are 6.2 times larger than that in the northeast region for the small–medium power plants. These results imply that an analysis that focuses only on the efficiency score would ignore the production scale of coal-fired thermal power plants and thus would fail to properly evaluate the environmental impacts associated with efficiency changes.
ABSTRACT
Escalating emissions of several air pollutants over South Asia could play a detrimental role in the regional and global atmosphere. Therefore, it is necessary to investigate these emissions within the boundary layer and at higher heights utilizing satellite data that are more inclusionary, where limited in situ observations are available. Here, we utilize the Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instruments (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment (GOME-2) hyperspectral satellite data to assess the changes in emission sources during Indian lockdown with a primary focus on the tropospheric profiles of ozone and carbon monoxide (CO). A significant reduction (> 20%) in the tropospheric ozone was seen over northern and northeast regions compared to 2018, while a dramatic increase (> 20%) compared to 2019 was seen. The subtropical dynamics mainly contributed to the increased ozone over the northern region. An analysis of the ozone production regime showed mostly NO2 limited regime over the major part of India and VOC limited regime over thermal power plants regions. Unlike in the boundary layer, where CO showed reduction (15-20%), CO profiles showed a consistent increase (as high as 31%) in the free troposphere over the majority of cities and thermal power plants. The CO total column also showed an increase (~ 20%) over central and western India and a slight decrease (5%) over northern India. Similar to CO, an increase (~ 15%) of NO2 column over the western region was observed particularly compared to 2019. However, unlike ozone and CO, reduction of tropospheric NO2 columns was seen over the major part of India, with the highest reduction over northern regions (20-52%). Furthermore, homogeneous yearly differences (> 30%) between OMI and TROPOMI NO2 observations were also seen distinctly over the remote areas. Contrary to surface-based studies, the present study shows an increase in CO, ozone (decrease), and NO2 at several locations and in the free troposphere during the lockdown.