Operational Planning of a Hybrid Power Plant for Off-Grid Mining Site: A Risk-constrained Optimization Approach

Castro, Gustavo Andres; Murkowska, Marta Irena; Rey, Pedro Zulaica; Anvari‐Moghaddam, Amjad

doi:10.1109/iecon43393.2020.9254402

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…Recent research completed with the software HOMER pro discusses the numerous solutions for meeting the mine's Western Australian electricity needs. A risk-constrained optimization technique is developed using Monte-Carlo uncertainty models to provide optimal scheduling, cost, and conditional value at risk (CVaR) [24]. A risk-constrained optimization technique using Monte-Carlo uncertainty models is developed for optimal scheduling and cost analysis of Western Australian mine's electricity needs.…”

Section: Uncertainty Handling In Microgrid Systemmentioning

confidence: 99%

A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques

Khan,

Haider,

Malik

et al. 2024

Processes

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The relentlessly depleting fossil-fuel-based energy resources worldwide have forbidden an imminent energy crisis that could severely impact the general population. This dire situation calls for the immediate exploitation of renewable energy resources to redress the balance between power consumption and generation. This manuscript confers about energy management tactics to optimize the methods of power production and consumption. Furthermore, this paper also discusses the solutions to enhance the reliability of the electrical power system. In order to elucidate the enhanced reliability of the electrical system, microgrids consisting of different energy resources, load types, and optimization techniques are comprehensively analyzed to explore the significance of energy management systems (EMSs) and demand response strategies. Subsequently, this paper discusses the role of EMS for the proper consumption of electrical power considering the advent of electric vehicles (EVs) in the energy market. The main reason to integrate EVs is the growing hazards of climate change due to carbon emissions. Moreover, this paper sheds light on the growing importance of artificial intelligence (AI) in the technological realm and its incorporation into electrical systems with the notion of strengthening existing smart grid technologies and to handle the uncertainties in load management. This paper also delineates the different methodologies to effectively mitigate the probability of facing cyber-attacks and to make the smart grids invulnerable.

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Section: Uncertainty Handling In Microgrid Systemmentioning

confidence: 99%

A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques

Khan,

Haider,

Malik

et al. 2024

Processes

View full text Add to dashboard Cite

show abstract

The Role of Integration of Hybrid Microgrids in Decarbonising Copper Deposits Mining in Australia

Huang,

Ata,

Rougieux

2024

Green Energy and Technology

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Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

Safari,

Daneshvar,

Anvari-Moghaddam

2024

Applied Sciences

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Artificial intelligence (AI) and machine learning (ML) can assist in the effective development of the power system by improving reliability and resilience. The rapid advancement of AI and ML is fundamentally transforming energy management systems (EMSs) across diverse industries, including areas such as prediction, fault detection, electricity markets, buildings, and electric vehicles (EVs). Consequently, to form a complete resource for cognitive energy management techniques, this review paper integrates findings from more than 200 scientific papers (45 reviews and more than 155 research studies) addressing the utilization of AI and ML in EMSs and its influence on the energy sector. The paper additionally investigates the essential features of smart grids, big data, and their integration with EMS, emphasizing their capacity to improve efficiency and reliability. Despite these advances, there are still additional challenges that remain, such as concerns regarding the privacy of data, challenges with integrating different systems, and issues related to scalability. The paper finishes by analyzing the problems and providing future perspectives on the ongoing development and use of AI in EMS.

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Operational Planning of a Hybrid Power Plant for Off-Grid Mining Site: A Risk-constrained Optimization Approach

Cited by 4 publications

References 14 publications

A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques

A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques

The Role of Integration of Hybrid Microgrids in Decarbonising Copper Deposits Mining in Australia

Energy Intelligence: A Systematic Review of Artificial Intelligence for Energy Management

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