1-13 of 13
Conference Theme: AI for Energy Sustainability
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

A Data-Driven Surrogate Modeling Optimization Framework for the Economic Dispatch of Microturbines Using Hydrogen Blends

Available to Purchase

David Thierry, Sarang Supekar, Chandrachur Bhattacharya, Joshua Christopher, Munidhar Biruduganti, Debolina Dasgupta, Sibendu Som
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A011, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131440
https://doi.org/10.1115/ES2024-131440
View Paper titled, A Data-Driven Surrogate Modeling Optimization Framework for the Economic Dispatch of Microturbines Using Hydrogen Blends
Open the PDF for A Data-Driven Surrogate Modeling Optimization Framework for the Economic Dispatch of Microturbines Using Hydrogen Blends in another window
Topics: Economics , Energy generation, Hydrogen, Metamodeling, Microturbines, Optimization
Proceedings Papers

Decentralized Condition Monitoring for Distributed Wind Systems: A Federated Learning-Based Approach to Enhance SCADA Data Privacy

Available to Purchase

Gang Li, Yusen Wu, Yelena Yesha
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A010, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131342
https://doi.org/10.1115/ES2024-131342
View Paper titled, Decentralized Condition Monitoring for Distributed Wind Systems: A Federated Learning-Based Approach to Enhance SCADA Data Privacy
Open the PDF for Decentralized Condition Monitoring for Distributed Wind Systems: A Federated Learning-Based Approach to Enhance SCADA Data Privacy in another window
Topics: Condition monitoring, Data privacy, Wind
Proceedings Papers

Improving Control of Energy Systems With Reinforcement Learning: Application to a Reversible Pump Turbine

Available to Purchase

Carlotta Tubeuf, Jakob aus der Schmitten, René Hofmann, Clemens Heitzinger, Felix Birkelbach
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A001, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-122475
https://doi.org/10.1115/ES2024-122475
View Paper titled, Improving Control of Energy Systems With Reinforcement Learning: Application to a Reversible Pump Turbine
Open the PDF for Improving Control of Energy Systems With Reinforcement Learning: Application to a Reversible Pump Turbine in another window
Topics: Energy / power systems, Process control, Pump turbines, Reinforcement learning
Proceedings Papers

Towards Improving High Spatiotemporal Weather Forecast Accuracy With Data-Driven Modeling

Available to Purchase

Shivesh Sharma, Maede Najian, Navid Goudarzi
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A012, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131519
https://doi.org/10.1115/ES2024-131519
View Paper titled, Towards Improving High Spatiotemporal Weather Forecast Accuracy With Data-Driven Modeling
Open the PDF for Towards Improving High Spatiotemporal Weather Forecast Accuracy With Data-Driven Modeling in another window
Topics: Modeling, Spatiotemporal phenomena, Weather forecasting, Artificial neural networks, Computational fluid dynamics, Resolution (Optics), Algorithms, Boundary-value problems, Cities, Engineering simulation
Proceedings Papers

Evaluating Reduced Order Models for Training Reinforcement Learning Agents for Building HVAC Control

Available to Purchase

Matthew Kerr, Bianca Howard
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A006, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-130508
https://doi.org/10.1115/ES2024-130508
View Paper titled, Evaluating Reduced Order Models for Training Reinforcement Learning Agents for Building HVAC Control
Open the PDF for Evaluating Reduced Order Models for Training Reinforcement Learning Agents for Building HVAC Control in another window
Topics: HVAC equipment, Reinforcement learning, Structures
Proceedings Papers

Machine Learning Based Assessment of the Air Quality Impacts From Natural Gas Production Facilities in Denton County, Texas

Available to Purchase

Jithin Kanayankottupoyil, Kuruvilla John
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A013, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131551
https://doi.org/10.1115/ES2024-131551
View Paper titled, Machine Learning Based Assessment of the Air Quality Impacts From Natural Gas Production Facilities in Denton County, Texas
Open the PDF for Machine Learning Based Assessment of the Air Quality Impacts From Natural Gas Production Facilities in Denton County, Texas in another window
Topics: Air pollution, Machine learning, Natural gas, Production facilities
Proceedings Papers

Machine Learning for Forecasting Solar Irradiance Using Satellite and Limited Ground Data

Available to Purchase

Jocellyn Luna, Alex Chancusig, Jose Cordova-Garcia, Guillermo Soriano
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A004, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-130057
https://doi.org/10.1115/ES2024-130057
View Paper titled, Machine Learning for Forecasting Solar Irradiance Using Satellite and Limited Ground Data
Open the PDF for Machine Learning for Forecasting Solar Irradiance Using Satellite and Limited Ground Data in another window
Topics: Machine learning, Satellites, Solar radiation, Solar energy, Meteorology, Irradiation (Radiation exposure), Artificial neural networks, Carbon footprint, Databases, Fossil fuels
Proceedings Papers

An Ultra-Short-Term Power Prediction Method for Wind Farms in Northwest China Based on Federated Learning

Available to Purchase

Wu Rong, Xiaojie Lin, Feiyun Cong, Wei Zhong
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A009, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131171
https://doi.org/10.1115/ES2024-131171
View Paper titled, An Ultra-Short-Term Power Prediction Method for Wind Farms in Northwest China Based on Federated Learning
Open the PDF for An Ultra-Short-Term Power Prediction Method for Wind Farms in Northwest China Based on Federated Learning in another window
Topics: China, Wind farms, Wind power, Carbon neutrality, Data privacy, Deep learning, Economics , Power grids, Wind power forecasting
Proceedings Papers

Efficiency-Driven Supervised Learning Regressors in Power Modeling and Optimization of Vertical Axis Wind Turbines

Available to Purchase

Ehsan Dorosti, Amir Shabani, Krishna Vijayaraghavan
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A003, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-124369
https://doi.org/10.1115/ES2024-124369
View Paper titled, Efficiency-Driven Supervised Learning Regressors in Power Modeling and Optimization of Vertical Axis Wind Turbines
Open the PDF for Efficiency-Driven Supervised Learning Regressors in Power Modeling and Optimization of Vertical Axis Wind Turbines in another window
Topics: Diffusers, Genetic algorithms, Machine learning, Modeling, Optimization, Support vector machines, Vertical axis wind turbines
Proceedings Papers

AI for Energy Intensive Industry: A Hybrid Optimization Approach for Flexibility Service Providers

Available to Purchase

Martin Fischer, René Hofmann
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A002, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-123705
https://doi.org/10.1115/ES2024-123705
View Paper titled, AI for Energy Intensive Industry: A Hybrid Optimization Approach for Flexibility Service Providers
Open the PDF for AI for Energy Intensive Industry: A Hybrid Optimization Approach for Flexibility Service Providers in another window
Topics: Genetic algorithms, Optimization, Particle swarm optimization
Proceedings Papers

Sensor Anomalies Characterization and Detection via Machine Learning Methods for Nuclear Power Plants

Available to Purchase

Liam M. Pohlmann, Palash K. Bhowmik, Congjian Wang, Piyush Sabharwall
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A008, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-131031
https://doi.org/10.1115/ES2024-131031
View Paper titled, Sensor Anomalies Characterization and Detection via Machine Learning Methods for Nuclear Power Plants
Open the PDF for Sensor Anomalies Characterization and Detection via Machine Learning Methods for Nuclear Power Plants in another window
Topics: Machine learning, Nuclear power stations, Nuclear reactors, Sensors
Proceedings Papers

Enhancing Battery Storage Energy Arbitrage With Deep Reinforcement Learning and Time-Series Forecasting

Available to Purchase

Manuel Sage, Joshua Campbell, Yaoyao Fiona Zhao
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A007, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-130538
https://doi.org/10.1115/ES2024-130538
View Paper titled, Enhancing Battery Storage Energy Arbitrage With Deep Reinforcement Learning and Time-Series Forecasting
Open the PDF for Enhancing Battery Storage Energy Arbitrage With Deep Reinforcement Learning and Time-Series Forecasting in another window
Topics: Batteries, Deep learning, Deep reinforcement learning, Storage, Time series
Proceedings Papers

A Deep Learning-Based Method for Non-Intrusive Load Monitoring and Load Disaggregation of 11kV/400V Electrical Substations

Available to Purchase

Elliott O’Malley, Daniel Pugh, Jianzhong Wu, David Clements
Proc. ASME. ES2024, ASME 2024 18th International Conference on Energy Sustainability, V001T01A005, July 15–17, 2024
Publisher: American Society of Mechanical Engineers
Paper No: ES2024-130477
https://doi.org/10.1115/ES2024-130477
View Paper titled, A Deep Learning-Based Method for Non-Intrusive Load Monitoring and Load Disaggregation of 11kV/400V Electrical Substations
Open the PDF for A Deep Learning-Based Method for Non-Intrusive Load Monitoring and Load Disaggregation of 11kV/400V Electrical Substations in another window
Topics: Stress