Earticle

초록

영어

Electric energy is the basic need for human survival on this earth as these needs increase with the rapid increase in population. It’s become a challenge to manage home energy with the current situation. Smart grid provided different techniques to overcome these challenges to meet the need. This paper presents the result of the different optimization techniques that give the best performance in reducing cost, PAR, and user discomfort. Based on results the best result techniques are also combined to make a hybrid model for more accuracy. This paper not only describes optimization techniques but also the limitations and features of these techniques.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
III. OVERVIEW OF DIFFERENT TECHNIQUES
A. Particle Swam Optimization (PSO)
B. Wind Driven Optimization (WDO)
C. Genetic Algorithm (GA)
D. Ant Colony Optimization (ACO)
E. Bacterial Foraging Optimization (BFO)
F. Artificial Neural Networks (ANN)
IV. ANALYSIS, DISCUSSION, AND RESULTS
V. CONCLUSION
REFERENCES

저자

• Taher M. Ghazal [ Center for Cyber Security, Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) ]
• Shahan Yamin Siddiqui [ School of Computer Science Minhaj University Lahore, 54000, Pakistan ]
• Muhammad Ubaidullah [ School of Computer Science Minhaj University Lahore, 54000, Pakistan ]
• Hafiz Muhammad Usama [ School of Computer Science Minhaj University Lahore, 54000, Pakistan ]
• Sidra Khan [ School of Computer Science Minhaj University Lahore, 54000, Pakistan ]
• Muhammad Adnan Khan [ Riphah School of Computing & Innovtion, Faculty of Computing, Riphah International University, Lahore Campus, 54000, Lahore, Pakistan ]

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