3 skills found
atmoschem / EixportExport Emissions to Atmospheric Models
Geraldine-Winston / Carbon Emission Forecasting Using LSTM Models.Harnessing LSTM neural networks, this project forecasts carbon emissions from historical data. Through streamlined preprocessing, dynamic modeling, and vivid visualizations, it transforms raw data into actionable, exportable insights for impactful environmental analysis and decision-making.
KULDEEP220 / Evaluation Project Global Power Plant Database TestAim: Need To Predict Primary Fuel And Capacity_mw For Global Power Plant Dataset. Problem Statment: An affordable, reliable, and environmentally sustainable power sector is central to modern society. Governments, utilities, and companies make decisions that both affect and depend on the power sector. For example, if governments apply a carbon price to electricity generation, it changes how plants run and which plants are built over time. On the other hand, each new plant affects the electricity generation mix, the reliability of the system, and system emissions. Plants also have significant impact on climate change, through carbon dioxide (CO2) emissions; on water stress, through water withdrawal and consumption; and on air quality, through sulfur oxides (SOx), nitrogen oxides (NOx), and particulate matter (PM) emissions. The Global Power Plant Database is an open-source open-access dataset of grid-scale (1 MW and greater) electricity generating facilities operating across the world. The actual Database currently contains nearly 35000 power plants in 167 countries, representing about 72% of the world's capacity. Entries are at the facility level only, generally defined as a single transmission grid connection point. Generation unit-level information is not currently available. But in our study we will be working on the dataset only for INDIA. The data set contains only 908 rows and 25 columns. The data set provides information of all the power plant situated at diffrent loactions in india. Features of dataset: country: symbolic country Name country_long: Full country Name name : Name of the Power Plant gppd_idnr : 10-12 character type ID of the power plant capacity_mw : Electricity generating capacity in megawatts latitude : Geo location of plant in decimal degerees longitude : Geo location of plant in decimal degerees primary_fuel : Primary fuel used for electricity genrration. other_fuel1 : Energy source used in electricity generation or export other_fuel2 : Energy source used in electricity generation or export other_fuel3 : Energy source used in electricity generation or export commissioning_year: year of opertaion of power plant or when the power plant start. owner : Majority shareholder of the power plant source: Entity reporting the data url : Web document corresponding to the sourcefield geolocation_source :Attribution for geolocation information wepp_id : A reference to a unique plant identifier in the widely-used PLATTS-WEPP database. year_of_capacity_data: year the capacity information was reported generation_gwh_2013 : electricity generation in gigawatt-hours reported for the year 2013 generation_gwh_2014 : electricity generation in gigawatt-hours reported for the year 2014 generation_gwh_2015 : electricity generation in gigawatt-hours reported for the year 2015 generation_gwh_2016 : electricity generation in gigawatt-hours reported for the year 2016 generation_gwh_2017 : electricity generation in gigawatt-hours reported for the year 2017 generation_data_source : electricity generation in gigawatt-hours reported for the year 2014 estimated_generation_gwh : attribution for the reported generation information
