Proficiency Assessment of Adaptive Neuro-Fuzzy Inference System to Predict Wind Power: A Case Study of Malaysia

Sarkar, Md Rasel; Nahar, Mst Jesmin; Nadia, Awatif; Halim, Md. Abdul; Rafin, S M Sajjad Hossain; Rahman, Md. Mamunur

doi:10.1109/icasert.2019.8934557

Cited by 6 publications

(5 citation statements)

References 22 publications

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“…Wind turbines [10], solar panels [11], and energy storage devices are examples of decentralized power sources that can be integrated [12] into smart networks. Reducing greenhouse gas emissions, they make it possible to integrate renewable energy sources into the system.…”

Section: Smart Gridmentioning

confidence: 99%

Technical and Economic Challenges and Future Prospects of a Smart Grid - A Case Study

Haque,

Hussain,

Ali

et al. 2024

Control Syst. Optim. Lett.

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In order to improve grid efficiency, dependability, and sustainability, smart grid technology is being developed and implemented at the vanguard of updating the world's electrical infrastructure. In addition to looking at the potential implications of smart grid technology, this case study analyzes the technical and financial difficulties encountered during the implementation of a smart grid. Technical issues with energy management and system stability arise when intermittent renewable energy sources are integrated into the smart grid. To make smooth transmission, sophisticated algorithms and grid management strategies are needed. Maintaining data security and privacy is crucial since smart grids mostly depend on digital technology and data exchange. It is a constant worry to defend the grid from hackers and illegal access. The installation of sensors, smart meters, and communication equipment might come with a significant initial cost when implementing a smart grid. One of the main economic challenges is financing these developments while maintaining reasonable power bills. It may be difficult to strike a balance between the interests of technology suppliers, customers, and utilities. Real-time monitoring and control are made possible by smart grids, which improve energy distribution and minimize energy waste. In addition to lowering greenhouse gas emissions, this improves overall energy efficiency. Smart grids can enable EV charging infrastructure as electric vehicle (EV) use increases, providing potential for grid optimization and new income streams for utilities. Reliability could be increased and downtime is decreased in a smart grid when defects can be promptly identified and isolated. The implementation of a smart grid is not without its technical and financial difficulties, but the future seems bright. Overcoming these obstacles may result in an electrical grid that is more sustainable, robust, and profitable for customers as well as utilities. Stakeholder cooperation, flexible regulations, and continuous technical development are needed to address these problems. By providing practical applications and real-world insights into the implementation of a smart grid, the case study acts as a link between theoretical concepts. Stakeholders obtain a comprehensive comprehension of the intricacies involved by analyzing technical and economic obstacles. To maximize the potential of smart grid technology, this knowledge is essential for fine-tuning strategies and creating focused solutions.

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Section: Smart Gridmentioning

confidence: 99%

Technical and Economic Challenges and Future Prospects of a Smart Grid - A Case Study

Haque,

Hussain,

Ali

et al. 2024

Control Syst. Optim. Lett.

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“…There are numerous ways to predict the amount of wind energy produced by a microgrid. Using numerical weather prediction (NWP) models [14], which simulate atmospheric conditions and forecast wind speed and direction for a specific place, is one popular strategy. Another strategy is to utilize machine learning algorithms to discover from historical data the patterns and connections between meteorological variables and wind energy generation [15].…”

Section: Wind Energy Generationmentioning

confidence: 99%

Microgrid Energy Management using Weather Forecasts: Case Study, Discussion and Challenges

Akter,

Islam,

Hasan

2023

IJRCS

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The main objective of this study is to demonstrate the integration of weather forecasts which can lead to a significant reduction in energy costs and carbon emissions while ensuring the reliability of the microgrid operation. By serving a small area or a particular building, the incorporation of weather forecasts can considerably increase the efficiency of microgrid energy management. The planning and operation of microgrids can be greatly improved by using weather predictions, which give useful information about upcoming weather conditions. By forecasting future energy demand and supply based on meteorological conditions, Microgrid Energy Management (MEM) is utilized to optimize the energy management decisions in microgrid systems. Making better choices regarding energy generation, storage, and consumption may be aided by the incorporation of weather forecasts, which can offer a more precise and trustworthy estimate of the energy demand and supply. This strategy can result in increased energy efficiency, decreased energy prices, and decreased carbon emissions, all of which are important goals for contemporary power systems. A promising approach for raising energy effectiveness and lowering greenhouse gas emissions in contemporary power networks is MEM. The incorporation of weather forecasts into MEM can improve decision-making regarding energy management by giving a better insight of future energy demand and supply. This essay examines the advantages and disadvantages of using weather forecasts in MEM through the presentation of a case example. By providing valuable information about future weather conditions, weather forecasts this review explain the Optimized Renewable Energy Integration, Improved Energy Storage Utilization, Load Shifting and Demand Response, Efficient Grid Management for reducing reliance on fossil fuels and lowering energy cost and carbon emissions. In order to address the issues related with MEM employing weather forecasts, this study offers potential fixes for increasing the accuracy of weather forecasts and emphasizes the necessity for more research in this area.

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“…We conducted a thorough review of eight published articles related to wind data prediction in Malaysia during 2005-2018 in the analyzed database. Four prediction methods used an artificial neural network (ANN) [94][95][96][97], two deployed an adaptive neuro-fuzzy inference system (ANFIS) [98,99], two used seasonal autoregressive integrated moving average (SARIMA) [81], and one used the Mycielski algorithm [100].…”

Section: Wind Predictionmentioning

confidence: 99%

“…Sahin and Erol [101] conducted a comparative analysis of both ANN and ANFIS concluding that the ANN approach performed better than the ANFIS model on predictions. Sarkar et al [99] also conducted a comparative study of wind power prediction using the ANFIS model in Kuala Lumpur and Melaka. Wind data were obtained from MMD over the period of 2013 to 2015.…”

Section: Wind Predictionmentioning

confidence: 99%

Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future Research Trends

et al. 2020

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In recent years, wind energy has gained extensive attention in the recent years in various countries due to the high energy demand of energy and shortage of traditional electric energy sources. Because wind energy constitutes a cost effective and environmentally friendly source, it can significantly contribute toward the reduction of the ever-increasing carbon emissions. It is one of the fastest growing green technologies worldwide, with a total generation share of 564 GW as of the end of 2018. In Malaysia, wind energy has been a hot topic in both academia and green energy industry. In this paper, the current status of wind energy research in Malaysia is reviewed. Different contributing factors such as potentiality and assessments, wind speed and direction modeling, wind prediction and spatial mapping, and optimal sizing of wind farms are extensively discussed. This paper discusses the progress of all studies related to wind energy and presents conclusions and recommendations for improving wind energy research in Malaysia.

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Proficiency Assessment of Adaptive Neuro-Fuzzy Inference System to Predict Wind Power: A Case Study of Malaysia

Cited by 6 publications

References 22 publications

Technical and Economic Challenges and Future Prospects of a Smart Grid - A Case Study

Technical and Economic Challenges and Future Prospects of a Smart Grid - A Case Study

Microgrid Energy Management using Weather Forecasts: Case Study, Discussion and Challenges

Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future Research Trends

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