Hybrid CNN-LSTM and Domain Modeling in Climate-Energy Analysis for a Smart Environment

Sarahana Shrestha, Brian Buckley, Aparna S. Varde, Daniel Cwynar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study aims to model the effect of local climate on energy generation in power plants in the United States. It considers climate change as well as the ever-growing electricity demand, contributing to greenhouse gas emissions. We propose an integration of AI-based and domain-specific paradigms via a hybrid approach of convolutional neural networks (CNN) & long short-term memory (LSTM) coupled with environmental models. Erstwhile studies focus mainly on specific energy sources, e.g. solar/wind power. There is a need for more comprehensive examination, e.g. temperature effects across various energy generation types at the macro level of states and micro level of power plants. This forms the major focus and novelty of our study. Fathoming the factors driving temperature-energy correlations, and assessing power plant vulnerability to changing climate patterns, are both essential to promote energy infrastructure resilience and sustainability. Our study offers novel insights into the complex interplay of temperature, energy generation, sustainability and related aspects to enable enhanced macro & micro level decision-making in energy sector. It therefore makes contributions to smart environment goals for smart cities and a smart planet.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 35th International Conference on Tools with Artificial Intelligence, ICTAI 2023
PublisherIEEE Computer Society
Pages229-233
Number of pages5
ISBN (Electronic)9798350342734
DOIs
StatePublished - 2023
Event35th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2023 - Atlanta, United States
Duration: 6 Nov 20238 Nov 2023

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (Print)1082-3409

Conference

Conference35th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2023
Country/TerritoryUnited States
CityAtlanta
Period6/11/238/11/23

Keywords

  • CNN
  • Climate Studies
  • Electricity
  • Energy
  • LSTM
  • Predictive Modeling
  • Smart Cities
  • Smart Environment

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