Data-Driven Classifier for Extreme Outage Prediction Based On Bayes Decision Theory
The growing concern over catastrophic weather events, mostly as a direct result of climate changes, has underscored the need for expanding traditional power system contingency analyses to handle the associated risks of extreme power outages. To enable power system operators to make timely decisions when facing extreme events, we explore in this paper the viability of a classifier which uses the machine learning approach based on the Bayes decision theory as a means of predicting power system component outages.
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Intra-Hour Photovoltaic Generation Forecasting Based on Multi-Source Data and Deep Learning Methods
Global issues pertaining to climate change have necessitated the rapid deployment of new energy sources, such as photovoltaic (PV) generation. In smart grids, accurate forecasting is essential to ensure the reliability and economy of the power system. However, PV generation is severely affected by meteorological factors, which hinders accurate forecasting. Various types of data, such as local measurement data, numerical weather prediction, and satellite images, can reflect meteorological dynamics over different time scales. This paper proposes a novel data-driven forecasting framework based on deep learning, which integrates an advanced U-net and an encoder-decoder architecture to cooperatively process multi-source (time series recording and satellite image) data.
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Wildfire Resiliency: California Case for Change
The world has seen an increase in catastrophic wildfires that have caused loss of lives, massive economic impacts from the properties and structures destroyed, and negative impacts on our environment and ecosystem. A recent study by the U.S. Geological Survey shows the greenhouse gas emissions from the 2018 California wildfires is on par with the entire year of equivalent emissions from all electricity generations combined feeding the needs of California.
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DAFT-E: Feature-Based Multivariate and Multi-Step-Ahead Wind Power Forecasting
At the recent 26th United Nations Climate Change Conference last year, more than 140 countries pledged to achieve net-zero emissions to combat climate change. And in a dramatic appeal to attain sustainability in the skies, Europe’s Flightpath 2050 initiated a bold effort to reduce CO2 emissions worldwide by 75%, NOx emissions by 90%, and the noise footprint by 60% by the midcentury mark.
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