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Detetion and Prevention of Irrelevent Data Through Data Cleansing

Published online https://doi.org/

Abstract

A file oriented unstructured data collected and transformed into the data warehouse .Two or more records identified separately actually represent same real world entity, detection and prevention to improve data quality. The proposed technique introduces smart tokens of most representative attributes by sorting those tokens identical records are bring into close neighborhood, record duplicates are identified and removed from the data. Clean consistent and non duplicated data loaded into warehouse. The technique is a mile stone for cleaning data as with the explosive amount of data recording it is the need of time that more corrected data to be provided to the data mangers for effective decisions making.

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Current Issue - 2024

Pilot Design of Aerated Windrow Composting by Green Waste: A Step towards Sustainable Energy

Vol. 11, Issue 12, PP. 210-217 December 2024

Published online https://doi.org/10.34259/ijew.24.1112210217

ePub PDF

Abstract

Sustainable solutions are required to address the growing problem of solid waste management (SWM) in urban areas, especially in developing countries. The objective of this study is to treat organic solid waste (OSW) from academic institutions by investigating the design and development of an effective pilot plant for aerated windrow composting. The research looks on turning food waste from campus canteens into nutrient-rich compost at the Department of Chemical Engineering at the University of Karachi. Under carefully monitored circumstances, the aerobic aerated windrow composting process optimized critical parameters like temperature, moisture content, pH, and the carbon-to-nitrogen (C: N) ratio. Microbial activity produced a notable reduction in trash volume over the course of the 60-day composting period. The finished compost had a (C: N) ratio of 30.3:1 and an ideal organic content of 58%. The thermophilic phase was successful, as seen by temperature profiles, peaking at 65°C and facilitating efficient pathogen elimination and nutrient stabilization. Acceptable amounts of potassium (1.44%), phosphorus (1.3%), and nitrogen (1.1%) were found in the laboratory, along with a pH of 8.5. These findings highlight the promise of aerated windrow composting as an economical and green way to handle urban garbage in tropical regions. The study concludes that implementing such composting systems in academic institutions can significantly mitigate the environmental impact of OSW. This research provides critical insights for policymakers and environmental engineers, supporting the development of large-scale composting initiatives to address waste management challenges in Karachi and similar urban environments.

Author

Sadaf Rani, Haroon Khan, Usama Abid

Cite

Sadaf Rani, Haroon Khan, Usama Abid “Pilot Design of Aerated Windrow Composting by Green Waste: A Step towards Sustainabl, Vol. 11, Issue 12, PP. 210-217, December 2024. https://doi.org/10.34259/ijew.24.1112210217., ,

References

P. Gupta, A. Sharma, and L. K. Bhardwaj, “Solid Waste Management (Swm) and Its Effect on Environment & Human Health,” Futur. Trends Agric. Eng. Food Sci. Vol. 3 B. 4, no. September, pp. 91–101, 2024, doi: 10.58532/v3bcag4p1ch7.
Forbes H.; Quested T.; O’Connor C., Food Waste Index Report 2021. 2021. [Online]. Available: https://www.unep.org/resources/report/unep-food-waste-index-report-2021
F. A. Azis, M. Rijal, H. Suhaimi, and P. E. Abas, “Patent Landscape of Composting Technology: A Review,” Inventions, vol. 7, no. 2, 2022, doi: 10.3390/inventions7020038.
A. Iqbal, Y. Abdullah, A. S. Nizami, I. A. Sultan, and F. Sharif, “Assessment of Solid Waste Management System in Pakistan and Sustainable Model from Environmental and Economic Perspective,” Sustain., vol. 14, no. 19, 2022, doi: 10.3390/su141912680.
A. Sanjrani, S. Rind, M. A. Sanjrani, and K. H. Shaikh, “Solid Waste Management: Environmental Impact and Solutions, Specially Focused on Pakistan,” J. Entrep. Manag. Innov., vol. 5, no. 1, 2023, doi: 10.52633/jemi.v5i1.
S. Khan, L. C. M. Alvarez, and Y. Wei, “Sustainable Management of Municipal Solid Waste Under Changing Climate : a Case Study of Karachi , Pakistan,” Asian J. Environ. Sci. Technol., vol. 2, no. 1, pp. 1–9, 2018.
A. A. Ananno, M. H. Masud, S. A. Chowdhury, P. Dabnichki, N. Ahmed, and A. M. E. Arefin, “Sustainable food waste management model for Bangladesh,” Sustain. Prod. Consum., vol. 27, pp. 35–51, 2021, doi: 10.1016/j.spc.2020.10.022.
W. Z. Khan, V. Inglezakis, S. Ishtiaque, and K. Moustakas, “Assessment of municipal solid waste management practices in Karachi City, Pakistan,” Int. J. Environ. Waste Manag., vol. 24, no. 2, pp. 131–150, 2019, doi: 10.1504/IJEWM.2019.101281.
A. Ahmed, A. Hussain, S. Thahrani, S. Ahmed, A. Q. Khoso, and B. Soomro, “Municipal Solid Waste Management and Waste to Energy in Karachi Pakistan †,” Eng. Proc., vol. 12, no. 1, 2021, doi: 10.3390/engproc2021012019.
N. Y. I. HASSAN, N. H. A. EL WAHED, A. N. ABDELHAMID, M. ASHRAF, and E. A. ABDELFATTAH, “Composting: an Eco-Friendly Solution for Organic Waste Management To Mitigate the Effects of Climate Change,” Innovare J. Soc. Sci., vol. 11, no. 4, pp. 1–7, 2023, doi: 10.22159/ijss.2023.v11i4.48529.

Advanced Optimization of PV Panel Cleaning Robot Based on Machine Learning Algorithms

Vol. 11, Issue 11, PP. 203-209 November 2024

Published online https://doi.org/10.34259/ijew.24.1111203209

ePub PDF

Abstract

This study introduces a robotic system designed to maintain photovoltaic (PV) panel efficiency by removing dust and debris that reduce energy output. The robot uses sensors and actuators to clean panels and adjusts its actions based on real-time environmental data. Engineered for efficiency and energy conservation, it includes cleaning brushes and movement modules. Machine learning techniques convolutional neural networks (CNNs) for detecting dust and reinforcement learning (RL) for optimizing movement paths enhance the robot adaptability. These algorithms enable it to balance dust removal effectiveness, energy use, and time efficiency, optimizing its cleaning strategy for sustainable PV panel maintenance.

Author

Shah Muhammad Adnan, Xu Wensheng, Muhammad Tahir Zaman,

Muhammad Aurangzeb, Fawwad Hassan Jaskani

Cite

Shah Muhammad Adnan, Xu Wensheng, Muhammad Tahir Zaman, Muhammad Aurangzeb, Fawwad Hassan Jaskani “Advanced Optimization of PV Panel Cleaning Robot Based on Machine Learni, Vol. 11, Issue 11, PP. 203-209, November 2024. https://doi.org/10.34259/ijew.24.1111203209., , , , ,

References

Al-Helal, I. M., Alhamdan, A. M., (2009). “Effect of arid environment on radiative properties of greenhouse polyethylene cover”, Solar Energy 83, 790-798.
Alshehri, A., Parrott, B., Outa, A., Amer, A., Abdellatif, F., Trigui, H., Carrasco, P., Patel, S., Taie, I.,“Dust mitigation in the desert: Cleaning mechanisms for solar panels in arid regions”, (2014).
Saudi Bouaouadja, N., Bouzid, S., Hamidouche, M., Bousbaa, C., Madjoubi, M., (2000). “Effects of sandblasting on the efficiencies of solar panels”, Applied Energy 65, 99-105.
Charfi, W., Chaabane, M., Mhiri, H., Bournot, P., (2018). “Performance evaluation of a solar photovoltaic system”, Energy Reports 4, 400-406. Ghazi, S., Sayigh, A., Ip, K., (2014). “Dust effect on flat surfaces–A review paper”, Renewable and Sustainable Energy Reviews 33, 742-751.
Gholami, A., Alemrajabi, A. A., Saboonchi, A., (2017). “Experimental study of self-cleaning property of titanium dioxide and nanospray coatings in solar applications”, Solar Energy 157, 559-565. He, G., Zhou, C., Li, Z., (2011). “Review of Self-Cleaning Method for Solar Cell Array”, Procedia Engineering 16, 640-645.
Kaldellis, J.K., Kapsali, M., (2011). “Simulating the dust effect on the energy performance of photovoltaic generators based on experimental measurements”, Energy 36, 5154-5161.
Kalogirou, S. A., Agathokleous, R., Panayiotou, G., (2013). “On-site PV characterization and the effect of soiling on their performance”, Energy 51, 439-446.
Charfi, W., Chaabane, M., Mhiri, H., Bournot, P., (2018). “Performance evaluation of a solar photovoltaic system”, Energy Reports 4, 400-406.
Maghami, M. R., Hizam, H., Gomes, C., Radzi, M. A., Rezadad, M. I., Hajighorbani, S., (2016). “Power loss due to soiling on solar panel: A review”, Renewable and Sustainable Energy Reviews 59, 1307-1316.
Jaradat, M. A., Tauseef, M., Altaf, Y., Saab, R., Adel, H., Yousuf, N., & Zurigat, Y. H. (2015). A fully portable robot system for cleaning solar panels. In 2015 10th International Symposium on Mechatronics and its Applications (ISMA) (pp. 1-6). IEEE.

Effect of Fly Ash and Silica Particles on Mechanical and Thermal Properties of A-356 alloy

Vol. 11, Issue 09, PP. 197-202 September 2024

Published online https://doi.org/10.34259/ijew.24.1109197202

ePub PDF

Abstract

This study investigates the effect of fly ash and silica particles on the mechanical and thermal properties of A-356 alloy. A-356, an aluminum alloy, is popular and has gained significant attention due to its lightweight and excellent mechanical properties. A-356 was reinforced with fly ash and silica at different weight percentages, and the composite was fabricated using a sand casting technique at around 660oC. hardness and thermal resistance tests were conducted, revealing a significant enhancement in hardness and thermal resistance with the addition of fly ash and silica particles. The microstructural analysis through S.E.M. and XRD showed a uniform distribution of fly ash and silica particles throughout the matrix.

Author

Arsalan, Feroz Shah, Quaid Jamal, Bilal Islam, Aizaz Ahmad Khan

Cite

Arsalan, Feroz Shah, Quaid Jamal, Bilal Islam, Aizaz Ahmad Khan “Effect of Fly Ash and Silica Particles on Mechanical and Thermal Properties , Vol. 11, Issue 09, PP. 197-202, September 2024. https://doi.org/10.34259/ijew.24.1109197202., , , ,

References

[1] K. Vijaya Bhaskar, S. Sundarrajan, M. Gopi Krishna, K. Ravindra Materials today: proceedings, 2017

[2] https://www.matweb.com/search/datasheet_print.aspx?matguid=d524d6bf305c4ce99414cabd1c7ed070

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[4] Babu Rao, J., Venkata Rao, D. and Bhargava, N.R.M.R. "Development of ALFA Lightweight Composites," International Journal of Engineering Science and Technology, Vol. 2, No. 11, pp. 50-59, 2010.

[5] Babu Rao, J., Venkata Rao, D. and Bhargava, N.R.M.R. "Development of ALFA Lightweight Composites," International Journal of Engineering Science and Technology, Vol. 2, No. 11, pp. 50-59, 2010.

[6] Rohatgi, P.K., Weiss, D. and Nikhil Gupta "Application of fly ash in the synthesis of low-cost metal matrix composites for automotive and other engineering applications," J.O.M., vol. 58, No. 11, pp. 71-76, 2006.

[7] LI Yue-ying, Cao Zhan Yi and Liu Yong Bing "Mechanical behavior of ZL109/Al2O3•SiO2 particle reinforced composites", Transactions of Nonferrous Metals Society of China, vol. 17, pp. 290-294, 2007.

[8] K.V. Mahindra, K. Radhakrishna, Materials Science-Poland, Vol. 25, No. 1, 2007

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[10] H.C. Anilkumar, H.S. Hebbar, K.S. Ravishankar, 2011, Mechanical Properties of Fly Ash Reinforced Aluminium Alloy (A16061) Composites International Journal of Mechanical and Materials Engineering (U.M.M.E.), Vol.6, 41-45

[11] 11.https://www.matweb.com/search/datasheet_print.aspx?matguid=d524d6bf305c4ce99414cabd1c7ed07

Prediction of Resilient Modulus of Subgrade Loamy Soils Through Wave Propagation Technique

Vol. 11, Issue 09, PP. 188-196 September 2024

Published online https://doi.org/10.34259/ijew.24.1109188196

ePub PDF

Abstract

The strength and performance of the subgrade are evaluated by its resilient modulus (MR) for the design of flexible pavement. The MR is routinely assessed using the cyclic triaxial test by conducting as per the American Association of State Highway and Transportation Officials (AASHTO). Since the triaxial test facility is not widely available and expensive, the proposed study intends to develop an MR relationship with CBR. For this purpose, eight disturbed soil samples were gathered from the Potohar region of Pakistan. The non-destructive test for MR measurement utilizing a new sonic viewer was performed before and after carrying out the CBR. The travel times of the compression (Vc) and shear (Vs) waves were also measured to calculate MR before and after each soaking period. A new empirical correlation between MR and CBR was developed using the ultrasonic pulse velocity (UPV) approach. This correlation was then evaluated by comparing it to past MR and CBR relationships, resulting in a strong agreement. Moreover, another excellent correlation was found between MR and compression wave velocity (Vc). It was also observed that larger compaction effort (blows/layer) influenced the linear increase in MR, Vc, and Vs values. Finally, UPV for predicting the MR of loamy soils for pavement design was more cost-effective and accurate than the conventional techniques which are complex and time taking.

Author

Usman Ali, Zakir Ullah, Muhammad Bilal, Sana Ullah

Cite

Usman Ali, Zakir Ullah, Muhammad Bilal, Sana Ullah “Prediction of Resilient Modulus of Subgrade Loamy Soils Through Wave Propagation Te, Vol. 11, Issue 09, PP. 188-196, September 2024. https://doi.org/10.34259/ijew.24.1109188196., ,

References

[1] Transportation Officials. (1993). AASHTO Guide for Design of Pavement Structures, 1993 (Vol. 1). Aashto.

[2] N. Thom, "Principles of pavement engineering". 2014.

[3] Seed, H. B., Chan, C. K., & Lee, C. E. (1962). Resilience characteristics of subgrade soils and their relation to fatigue failures in asphalt pavements. In International Conference on the Structural Design of Asphalt Pavements. Supplement University of Michigan, Ann Arbor.

[4] Y. H. Huan, (2004) "Pavement Analysis and Design Second Edition." ISBN 13: 9780131424739.

[5] AASHTO (1994). Standard Method of Test for Resilient Modulus of Unbound Granular Base/Subbase Materials and Subgrade Soils. AASHTO Designation: T 294, 1994.

[6] Kirwan, R. W., & Snaith, M. S. (1976). "A simple chart for the prediction of resilient modulus". Geotechnique, 26(1), 212-215.

[7] W. Sas, A. Gluchowski, K. Gabryś, E. Soból, and A. Szymanski, "Resilient modulus characterization of compacted cohesive subgrade soil," Applied Sciences (Switzerland), vol. 7, no. 4, Apr. 2017, doi: 10.3390/app7040370.

[8] Wright, P.H. 1996. Highway Engineering 6th Wiley, New York.

[9] R. A. Khalid, N. Ahmad, M. U. Arshid, S. B. Zaidi, T. Maqsood, and A. Hamid, "Performance evaluation of weak subgrade soil under increased surcharge weight," Constr Build Mater, vol. 318, Feb. 2022, doi: 10.1016/j.conbuildmat.2021.126131.

[10] Heukelom, W., and AsJG Klomp. "Dynamic testing as a means of controlling pavements during and after construction." In International Conference on the Structural Design of Asphalt Pavements University of Michigan, Ann Arbor, vol. 203, no. 1. 1962

Enhancing Quality and Reducing Wastage in ATN Soap Industry Peshawar Using Six Sigma and Artificial Intelligence (AI)

Vol. 11, Issue 09, PP. 177-187 September 2024

Published online https://doi.org/10.34259/ijew.24.1109177187

ePub PDF

Abstract

Peshawar ATN Soap Industry is confronted with issues pertaining to substandard quality and ineffective waste management, which influence overall operational performance. This study suggests a thorough strategy that combines artificial intelligence (AI) and Six Sigma methodology to address these problems. AI technology will be used to improve predictive maintenance, maximize resource usage, and eliminate defects; Six Sigma techniques will be used to discover and reduce variances in the soap production process. The research will begin with a thorough examination of the way things are now run, highlighting major issues with waste management and quality. The soap production process will be systematically analyzed and improved through the application of Six Sigma techniques, such as the DMAIC (Define, Measure, Analyze, Improve, and Control) methodology. To do this, quantifiable targets must be defined, pertinent data must be gathered, and focused changes must be put into place to get rid of flaws and increase the overall quality of the product. In the context of the ATN Soap Industry, the research seeks to illustrate the synergistic benefits of combining Six Sigma and AI. Significant gains in product quality, a decrease in defects, increased operational effectiveness, and a sustainable waste management strategy are among the anticipated results. This all-encompassing strategy can help improve industrial procedures in the area by acting as a model for other businesses dealing with comparable issues.

Author

Syed Muhammad Shakir Bukhari, Rehman Akhtar

Cite

Syed Muhammad Shakir Bukhari, Rehman Akhtar “Enhancing Quality and Reducing Wastage in ATN Soap Industry Peshawar Using Six Sigma and Artificial Intelligence (AI)” International Journal of Engineering Works, Vol. 11, Issue 09, PP. 177-187, September 2024. https://doi.org/10.34259/ijew.24.1109177187.

References

[1] Harry, M., & Schroeder, R. (2000). Six Sigma: The Breakthrough Management Strategy Revolutionizing the World Top Corporations. Doubleday.

[2] Ross, P. (2019). Artificial Intelligence: A Guide for Thinking Humans. Little, Brown Spark.

[3] Pyzdek, T., & Keller, P. A. (2014). The Six Sigma Handbook. McGraw-Hill Education.

[4] Davenport, T. H., & Harris, J. (2007). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.

[5] M. Mohan Prasad, J. M. Dhiyaneswari, J. Ridzwanul Jamaan, S. Mythreyan, and S. M. Sutharsan, “A framework for lean manufacturing implementation in Indian textile industry,” Materials Today: Proceedings, vol. 33, pp. 2986–2995, Jan. 2020, doi: 10.1016/j.matpr.2020.02.979.

[6] N. Kumar, S. Shahzeb Hasan, K. Srivastava, R. Akhtar, R. Kumar Yadav, and V. K. Choubey, “Lean manufacturing techniques and its implementation: A review,” Materials Today: Proceedings, vol. 64, pp. 1188–1192, Jan. 2022, doi: 10.1016/j.matpr.2022.03.481.

[7] S. Vinodh, S. V. Kumar, and K. E. K. Vimal, “Implementing lean sigma in an Indian rotary switches manufacturing organisation,” Production Planning & Control, vol. 25, no. 4, pp. 288–302, Mar. 2014, doi: 10.1080/09537287.2012.684726.

[8] J. Bhamu and K. Singh Sangwan, “Lean manufacturing: literature review and research issues,” International Journal of Operations & Production Management, vol. 34, no. 7, pp. 876–940, Jan. 2014, doi: 10.1108/IJOPM-08-2012-0315.

[9] “Possibilities of Maintenance Service Process Analyses and Improvement Through Six Sigma, Lean and Industry 4.0 Implementation | SpringerLink.” Accessed: Sep. 24, 2023. [Online]. Available: https://link.springer.com/chapter/10.1007/978-3-030-01614- 2_43

[10] EV Gijo, J Scaria, J Antony, “Application of six sigma methodology to reduce defects of a grinding process". Quality and Reliability Engineering International, Vol. 27, pp. 1221-1234, 4 May, 2011, doi: doi.org/10.1002/qre.1212

Design and Fabrication of Low-Cost 3D Scanner Based on Photogrammetry for Mechanical Components

Vol. 11, Issue 09, PP. 171-176 September 2024

Published online https://doi.org/10.34259/ijew.24.1109171176

ePub PDF

Abstract

Photogrammetry is a technique used to create a virtual 3D model of objects using photos of an object. A 3D scanner in photogrammetry employs a specific methodology to capture the necessary data and generate accurate 3D models by collecting points from images taken from different angles. Various techniques have been proposed for 3D scanning, which are not easy to use. These require expensive 3D scanners and much time for processing. Therefore, a new fabrication of 3D scanning is required to perform scanning very quickly and efficiently. The proposed photogrammetry approach can enable manufacturing industries to make 3D models of any object efficiently and rapidly. For demonstration, a case study of piston scanning was selected. For this purpose, a smartphone camera is used first to take pictures of the gear from multiple angles. These pictures were then uploaded to Agisoft Metashape Professional to create its 3D scan. The dimensions of this 3D scan were compared to the original part, which showed a deviation of only 0.021 mm, demonstrating its reasonable application for a mechanical component. Finally, using Geomagic Design X, this scan was used to create a one-to-one 3D model of the piston.

Author

Izaz Ul Haq, Prof. Dr. Sahar Noor, Engr. Zeeshan Ahmad, Engr. Muhammad Umair Khan

Cite

Izaz Ul Haq, Prof. Dr. Sahar Noor, Engr. Zeeshan Ahmad, Muhammad Umair Khan “Design and Fabrication of Low-Cost 3D Scanner Based on Photogrammetry for M, Vol. 11, Issue 09, PP. 171-176, September 2024. https://doi.org/10.34259/ijew.24.1109171176., ,

References

[1] Haleem, A.; Javaid, M.; Singh, R.P.; Rab, S.; Suman, R.; Kumar, L.; Khan, I.H. Exploring the Potential of 3D Scanning in Industry 4.0: An Overview. Int. J. Cogn. Comput. Eng. 2022, 3, 161–171, doi:https://doi.org/10.1016/j.ijcce.2022.08.003.

[2] Javaid, M.; Haleem, A.; Singh, R.P.; Suman, R. Industrial Perspectives of 3D Scanning: Features, Roles and Its Analytical Applications. Sensors Int. 2021, 2, 100114.

[3] Ding, N.; Zhang, G.; Zhang, L.; Shen, Z.; Yin, L.; Zhou, S.; Deng, Y. Engineering an AI-Based Forward-Reverse Platform for the Design of Cross-Ribosome Binding Sites of a Transcription Factor Biosensor. Comput. Struct. Biotechnol. J. 2023, 21, 2929–2939, doi:https://doi.org/10.1016/j.csbj.2023.04.026.

[4] Helle, R.H.; Lemu, H.G. A Case Study on Use of 3D Scanning for Reverse Engineering and Quality Control. Mater. Today Proc. 2021, 45, 5255–5262.

[5] Javaid, M.; Haleem, A.; Singh, R.P.; Rab, S.; Suman, R.; Kumar, R. Studies on the Metrological Need and Capabilities of 3D Scanning Technologies. J. Ind. Integr. Manag. 2023, 8, 321–339.

[6] Jarahizadeh, S.; Salehi, B. A Comparative Analysis of UAV Photogrammetric Software Performance for Forest 3D Modeling: A Case Study Using AgiSoft Photoscan, PIX4DMapper, and DJI Terra. Sensors 2024, 24, 286.

[7] Georgopoulos, A.; Stathopoulou, E.K. Data Acquisition for 3D Geometric Recording: State of the Art and Recent Innovations. Herit. Archaeol. Digit. age Acquis. curation, Dissem. Spat. Cult. Herit. data 2017, 1–26.

[8] Luhmann, T. Close Range Photogrammetry for Industrial Applications. ISPRS J. Photogramm. Remote Sens. 2010, 65, 558–569.

[9] KANUN, E. Using Photogrammetric Modeling in Reverse Engineering Applications: Damaged Turbocharger Example. Mersin Photogramm. J. 2021, 3, 21–28, doi:10.53093/mephoj.901188.

[10] KANUN, E.; KANUN, G.M.; YAKAR, M. 3D Modeling of Car Parts by Photogrammetric Methods: Example of Brake Discs. Mersin Photogramm. J. 2022, 4, 7–13, doi:10.53093/mephoj.1131619

Enhancing Energy Security in Pakistan through Smart Grid Technology and Dynamic Scheduling

Vol. 11, Issue 09, PP. 165-170 September 2024

Published online https://doi.org/10.34259/ijew.24.1109165170

ePub PDF

Abstract

The increasing global demand for electricity, coupled with the imperative to reduce greenhouse gas emissions, has propelled the transformation of traditional power grids into intelligent and adaptive systems known as Smart Grids. At the heart of this transformation lies Dynamic Load Scheduling (DLS), an innovative approach that seeks to enhance grid efficiency, optimize energy utilization, and foster grid resiliency. This study undertakes a comprehensive exploration of DLS within the context of a Smart Grid scenario, employing a mixed-methods research approach encompassing literature reviews, case studies, quantitative analysis. The study outcomes contribute to the growing body of knowledge on Smart Grid technologies, specifically highlighting the pivotal role that DLS plays in transforming the future of electrical power systems. With the potential to revolutionize energy management strategies, DLS within Smart Grids emerges as a cornerstone for sustainable, reliable, and resilient energy systems. This research offers a roadmap for policymakers, utilities, and researchers to navigate the complex landscape of Smart Grids and harness the transformative power of Dynamic Load Scheduling. This abstract provides a concise overview of the detailed exploration of Dynamic Load Scheduling in Smart Grids and its role in offering different dynamics.

Author

Umar Khayam, Muhammad Umair, Farhan Ullah

Cite

Umar Khayam, Muhammad Umair, Farhan Ullah “Enhancing Energy Security in Pakistan through Smart Grid Technology and Dynamic Sc, Vol. 11, Issue 09, PP. 165-170, September 2024. https://doi.org/10.34259/ijew.24.1109165170., ,

References

[1] World Energy Council (WEC), "World Energy Council definition of energy security," [Online]. Available: https://www.worldenergy.org/. [Accessed: May 12, 2024].

[2] Pakistan Integrated Energy Plan (IGCEP) 2047, Government of Pakistan.

[3] "Pakistan Energy Statistics 2019," Pakistan Energy Information Administration (PEIA).

[4] International Energy Agency (IEA), "Smart Grids: Core Elements," [Online]. Available: https://www.iea.org/reports/smart-grids-core-elements. [Accessed: May 12, 2024]

[5] Smart Electric Power Alliance (SEPA), "Smart Grid Benefits," [Online]. Available: https://sepapower.org/our-work/smart-grid/. [Accessed: May 12, 2024].

[6] Electric Power Research Institute (EPRI), "Smart Grid Research," [Online]. Available: https://www.epri.com/research/areas-of-focus/smart-grid. [Accessed: May 12, 2024]

[7] Institute of Electrical and Electronics Engineers (IEEE), "Dynamic Scheduling in Smart Grids," [Online]. Available: https://ieeexplore.ieee.org/. [Accessed: May 12, 2024].

[8] Zhang, Y., Chen, Y., Fu, Y., & Zhang, Y. (2019). Blockchain Based Energy Trading Platform for Microgrid. In 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (pp. 1-6). IEEE.

[9] Liang, Y., Shi, L., Hu, X., & Huang, Y. (2020). A Blockchain-enabled Demand Response Mechanism for Microgrids. In 2020 IEEE International Conference on Smart Grid Communications (SmartGridComm) (pp. 1-6). IEEE.

[10] Wang, J., Xiong, W., Yang, Y., & Han, Z. (2021). Blockchain-Enabled Dynamic Load Scheduling for Microgrids with IoT Integration. IEEE Internet of Things Journal, 8(1), 398-407

[11] Zeng, Y., Zhang, H., Gjessing, S., & Zhou, J. (2021). Challenges and Opportunities of Blockchain for Energy Management in Microgrids: A Review. IEEE Access, 9, 53603-53620.

[12] Jamil et al., 2017, Jamil Irfan, Zhao Jinquan, Zhang Li, et al. Evaluation of energy production and energy yield assessment based on feasibility, design, and execution of 350 MW grid-connected solar PV pilot project in Nooriabad"

Solving System of Highly Oscillatory Ordinary Differential Equations with Residual-based Adaptive Refinement of Physics-Informed Neural Networks

Vol. 11, Issue 09, PP. 160-164 September 2024

Published online https://doi.org/10.34259/ijew.24.1109160164

ePub PDF

Abstract

This paper presents an innovative method for solving systems of ordinary differential equations (ODEs) characterized by oscillatory solutions, utilizing Residual-Based Adaptive Refinement of Physics-Informed Neural Networks (RAR-PINNs). Conventional numerical techniques often face challenges in accurately resolving oscillatory solutions due to issues with convergence and stability. To address these challenges, we introduce a refined approach that integrates adaptive refinement strategies with physics-informed neural networks, enhancing their capability to model and predict complex oscillatory dynamics. Our method involves an adaptive mechanism that selectively refines the neural network focus based on the residual errors of the predicted solutions, thereby improving accuracy where it is most needed. By incorporating physical constraints directly into the learning process, our approach ensures that the neural network not only captures the underlying oscillatory patterns but also adheres to the governing differential equations. We validate the effectiveness of the RAR-PINNs approach through numerical experiments on benchmark problems with known oscillatory solutions, demonstrating substantial improvements in both solution accuracy and computational efficiency compared to traditional methods. This advancement provides a powerful tool for tackling highly oscillatory ODE systems in various scientific and engineering applications where oscillatory behavior is prevalent.

Author

Ghani Irfan, Haider Zaman, Muhammad Ishaq, Wajid Khan

Cite

Ghani Irfan, Haider Zaman, Muhammad Ishaq, Wajid Khan “Solving System of Highly Oscillatory Ordinary Differential Equations with Residu, Vol. 11, Issue 09, PP. 160-164, September 2024. https://doi.org/10.34259/ijew.24.1109160164., , ,

References

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Pilot Design of Aerated Windrow Composting by Green Waste: A Step towards Sustainable Energy

Vol. 11, Issue 12, PP. 210-217 December 2024

Published online https://doi.org/10.34259/ijew.24.1112210217

ePub PDF

Abstract

Author

Sadaf Rani, Haroon Khan, Usama Abid

Cite

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Advanced Optimization of PV Panel Cleaning Robot Based on Machine Learning Algorithms

Vol. 11, Issue 11, PP. 203-209 November 2024

Published online https://doi.org/10.34259/ijew.24.1111203209

ePub PDF

Abstract

Author

Shah Muhammad Adnan, Xu Wensheng, Muhammad Tahir Zaman,

Muhammad Aurangzeb, Fawwad Hassan Jaskani

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