Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach
The mining industry is a key contributor to Western Australia’s economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportu...
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2024-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/17/22/5679 |
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| author | Mehrdad Ghahramani Daryoush Habibi Seyyedmorteza Ghamari Asma Aziz |
| author_facet | Mehrdad Ghahramani Daryoush Habibi Seyyedmorteza Ghamari Asma Aziz |
| author_sort | Mehrdad Ghahramani |
| collection | DOAJ |
| description | The mining industry is a key contributor to Western Australia’s economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportunities of integrating renewable energy sources into isolated power systems, particularly under uncertainties associated with renewable energy generation and demand. A robust optimization approach is developed to model a multi-source hybrid energy system that considers risk-averse, risk-neutral, and risk-seeking strategies. These strategies address power demand and renewable energy supply uncertainties, ensuring system reliability under various risk scenarios. The optimization framework, formulated as a mixed integer linear programming problem and implemented in Python using the Gurobi Optimizer, integrates renewable energy sources such as wind turbines, photovoltaic arrays, and demand response programs alongside traditional diesel generators, boilers, combined heat and power units, and water desalination. The model ensures reliable access to electricity, heat, and water while minimizing operational costs and reducing reliance on fossil fuels. A comprehensive sensitivity analysis further examines the impact of uncertainty margins and the value of a lost load on the total system cost, providing insights into how different risk strategies affect system performance and cost-efficiency. The results are validated through three case studies demonstrating the effectiveness of the proposed approach in enhancing the resilience and sustainability of isolated power systems in the mining sector. Significant improvements in reliability, scalability, and economic performance are observed, with the sensitivity analysis highlighting the critical trade-offs between cost and reliability under varying uncertainty conditions. |
| format | Article |
| id | doaj-art-6f70b18648a944608df335f28b64d8b5 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-6f70b18648a944608df335f28b64d8b52025-08-20T02:08:03ZengMDPI AGEnergies1996-10732024-11-011722567910.3390/en17225679Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization ApproachMehrdad Ghahramani0Daryoush Habibi1Seyyedmorteza Ghamari2Asma Aziz3School of Engineering, Edith Cowan University, Joondalup, WA 6027, AustraliaSchool of Engineering, Edith Cowan University, Joondalup, WA 6027, AustraliaSchool of Engineering, Edith Cowan University, Joondalup, WA 6027, AustraliaSchool of Engineering, Edith Cowan University, Joondalup, WA 6027, AustraliaThe mining industry is a key contributor to Western Australia’s economy, with over 130 mining operations that produce critical minerals such as iron ore, gold, and lithium. Ensuring a reliable and continuous energy supply is vital for these operations. This paper addresses the challenges and opportunities of integrating renewable energy sources into isolated power systems, particularly under uncertainties associated with renewable energy generation and demand. A robust optimization approach is developed to model a multi-source hybrid energy system that considers risk-averse, risk-neutral, and risk-seeking strategies. These strategies address power demand and renewable energy supply uncertainties, ensuring system reliability under various risk scenarios. The optimization framework, formulated as a mixed integer linear programming problem and implemented in Python using the Gurobi Optimizer, integrates renewable energy sources such as wind turbines, photovoltaic arrays, and demand response programs alongside traditional diesel generators, boilers, combined heat and power units, and water desalination. The model ensures reliable access to electricity, heat, and water while minimizing operational costs and reducing reliance on fossil fuels. A comprehensive sensitivity analysis further examines the impact of uncertainty margins and the value of a lost load on the total system cost, providing insights into how different risk strategies affect system performance and cost-efficiency. The results are validated through three case studies demonstrating the effectiveness of the proposed approach in enhancing the resilience and sustainability of isolated power systems in the mining sector. Significant improvements in reliability, scalability, and economic performance are observed, with the sensitivity analysis highlighting the critical trade-offs between cost and reliability under varying uncertainty conditions.https://www.mdpi.com/1996-1073/17/22/5679robust optimizationhybrid energy systemsrenewable energy integrationstand-alone power systemmining sector energydemand response |
| spellingShingle | Mehrdad Ghahramani Daryoush Habibi Seyyedmorteza Ghamari Asma Aziz Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach Energies robust optimization hybrid energy systems renewable energy integration stand-alone power system mining sector energy demand response |
| title | Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach |
| title_full | Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach |
| title_fullStr | Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach |
| title_full_unstemmed | Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach |
| title_short | Addressing Uncertainty in Renewable Energy Integration for Western Australia’s Mining Sector: A Robust Optimization Approach |
| title_sort | addressing uncertainty in renewable energy integration for western australia s mining sector a robust optimization approach |
| topic | robust optimization hybrid energy systems renewable energy integration stand-alone power system mining sector energy demand response |
| url | https://www.mdpi.com/1996-1073/17/22/5679 |
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