Electricity generation, natural gas consumption and CO2 emission data of a power plant in Dhaka, Bangladesh
Description
This study collected fuel consumption and electricity generation data from an engine-based natural gas-fired power plant in Dhaka Export Processing Zone Authority (DEPZ), Bangladesh. In this study, CO2 emission was calculated using IPCC 2006 guidelines from fuel consumption data from 2015 to 2022. This data will be helpful in further study and in the preparation of emission forecasting and emission reduction strategies. CO2 Emission forecasting is an important tool for predicting future levels of greenhouse gas emissions. It helps us understand the impact of human activities like power generation, fuel burn on the environment, and climate change. By analyzing past trends and current data, this study will make informed decisions about reducing emissions and mitigating the effects of climate change. Accurate emission forecasts are essential for National and international policymakers, businesses, and individuals to develop effective strategies for reducing emissions and transitioning to a more sustainable future. However, this dataset also included forecasted dataset for 2023- 2026. Forecasting uses the Linear Extrem Learning Machine (LELM) model in Rsudio. Rscript and historical datasets with predicted data presented here. In Version 4 CO2 emissions historical data anomaly also added.