Abstract
The depletion of hydrocarbon supplies has spurred a global paradigm shift toward renewable energy sources, generating an urgent need for creative solutions that can satisfy the energy demands of cities in a sustainable manner. In this context, the development of an AI-powered energy forecasting tool is a viable way to addressing the complex difficulties of urban energy management. This research focuses on explaining the technique and critical components of such a tool, which is critical in providing exact projections for energy generation in urban areas. The major focus is on the use of solar and wind energy for hydrogen synthesis. The creation of this AI tool necessitates a careful data processing approach that includes the acquisition and analysis of a full 12-month dataset including all seasons. This information is critical since it serves as the foundation for assuring the accuracy of energy availability projections. It compensates for variations in solar irradiation, which is crucial for solar energy, and wind speed, which is critical for wind energy. The program can offer realistic estimates that account for the intermittent nature of renewable energy sources by including these dynamic characteristics. This enables urban planners to make well-informed judgments about maximizing energy consumption, resulting in a more sustainable and efficient urban energy environment. The synthesis of hydrogen using proton exchange membrane (PEM) electrolyzers is one of the principal uses of the AI-driven instrument. As renewable energy sources such as sun and wind vary, excess energy may be transferred to PEM electrolyzers, where water is electrolyzed to produce hydrogen. The quantity of hydrogen generated by a hybrid solar and wind energy system is expected to be 3.5 kg/day to 21 kg/day. This sustainable hydrogen generation provides a possible method for efficiently storing and using excess renewable energy, hence boosting energy sustainability in urban settings.
| Original language | English |
|---|---|
| Title of host publication | 2023 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350330816 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
| Event | 3rd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2023 - Islamabad, Pakistan Duration: 3 Oct 2023 → 4 Oct 2023 |
Publication series
| Name | 2023 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2023 |
|---|
Conference
| Conference | 3rd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2023 |
|---|---|
| Country/Territory | Pakistan |
| City | Islamabad |
| Period | 3/10/23 → 4/10/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Hybrid system
- Hydrogen Power
- Machine Learning
- Renewable Energy Sources
- Solar and Wind
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Safety, Risk, Reliability and Quality
- Electrical and Electronic Engineering
Fingerprint
Dive into the research topics of 'Shifting Energy Horizons: Utilizing AI-Driven Energy Forecasting for Hydrogen Production in Urban Environments'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver