원문정보
한국차세대컴퓨팅학회
한국차세대컴퓨팅학회 학술대회
The 8th International Conference on Next Generation Computing 2022
2022.10
pp.68-71
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보