Logo

RNfinity

Login Register
  • News/Blog
  • View
  • Info
  • Submit
  • Contact Us
  • Home

Physics Maths Engineering

Empowering Optimal Operations with Renewable Energy Solutions for Grid Connected Merredin WA Mining Sector

rnfinity

info@rnfinity.com

orcid logo

Md Ohirul Qays,

Md Ohirul Qays

School of Engineering, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia


Ravi Kumar,

Ravi Kumar

School of Engineering, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia


Minhaz Ahmed,

Minhaz Ahmed

School of Engineering, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia


Stefan Lachowicz,

Stefan Lachowicz

School of Engineering, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia


Uzma Amin

Uzma Amin

School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, WA 6102, Australia


  Peer Reviewed

copyright icon

© attribution CC-BY

  • 0

rating
6 Views

Added on

2025-08-17

Doi: https://doi.org/10.3390/app15105516

Abstract

Mining sectors require a continuous and reliable power supply; however, reliance on traditional grid utilities results in high costs and disruptions and increases extreme carbon emission. The Merredin WA sector seeks to resolve critical energy challenges affecting mining operations in Western Australia. Thus, this research proposes an optimal solar PV system with battery storage and backup generation for the mining sector to ensure a stable and cost-effective power supply that reduces harmful environmental effect. A hybrid data-driven long short-term memory (LSTM)-classical optimization framework is designed here, thereby optimizing PV-battery storage operational cost savings and energy usage. The optimization results indicate that approximately 57% of load demand can be fulfilled by the proposed optimal PV system with future cost savings of USD $8627.53 per annum. The optimization method also resulted in the lowest computation time of 1.153 s and highest accuracy 99.247% when compared with other existing algorithms. Furthermore, the integration of renewable energy (RE) technologies within mining operations substantially reduces carbon emissions by 67%, thus contributing to broader global sustainability purposes. The study presents a sustainable and economically viable energy solution for mining operations, setting a precedent for RE adoption in remote and energy-intensive industries.

Summary Video Not Available

Review 0

Login

ARTICLE USAGE


Article usage: Aug-2025 to Aug-2025
Show by month Manuscript Video Summary
2025 August 6 6
Total 6 6
Show by month Manuscript Video Summary
2025 August 6 6
Total 6 6
Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology
copyright icon

© attribution CC-BY

  • 0

rating
6 Views

Added on

2025-08-17

Doi: https://doi.org/10.3390/app15105516

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

Follow Us

  • Xicon
  • Contact Us
  • Privacy Policy
  • Terms and Conditions

5 Braemore Court, London EN4 0AE | Telephone +442082758777 | info@rnfinity.com |


© Copyright 2025 All Rights Reserved.