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Introduction

The accurate forecasting of power system load is crucial for the efficient and reliable operation of power systems. Load forecasting plays a key role in various aspects of power system operations, including economic dispatch, unit commitment, and energy scheduling. With the increasing integration of renewable energy sources and the growing complexity of modern power systems, accurate load forecasting has become even more challenging. This study aims to analyze the different techniques and methodologies used for power system load forecasting, with a focus on improving the accuracy and reliability of these forecasts.

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter Two: Literature Review
2.1 Overview of Load Forecasting
2.2 Types of Load Forecasting Techniques
2.3 Traditional Methods of Load Forecasting
2.4 Advanced Techniques for Load Forecasting
2.5 Challenges in Load Forecasting
2.6 Applications of Load Forecasting in Power Systems
2.7 Accuracy Metrics for Load Forecasting
2.8 Machine Learning Approaches for Load Forecasting
2.9 Time Series Analysis for Load Forecasting
2.10 Comparative Analysis of Load Forecasting Techniques

Chapter Three: System Design and Methodology
3.1 Data Collection for Load Forecasting
3.2 Preprocessing of Data for Load Forecasting
3.3 Feature Extraction for Load Forecasting
3.4 Model Selection for Load Forecasting
3.5 Training and Validation of Load Forecasting Models
3.6 Performance Evaluation of Load Forecasting Models
3.7 Ensemble Forecasting Techniques
3.8 Hybrid Forecasting Models

Chapter Four: System Implementation
4.1 Implementation of Load Forecasting Models
4.2 Integration with Power System Operations
4.3 Real-Time Load Forecasting
4.4 Case Studies and Experiments
4.5 Evaluation of Implemented System
4.6 Comparison with Existing Systems
4.7 Scalability and Performance of Implemented System
4.8 Future Enhancements and Extensions

Chapter Five: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Implications for Power System Operations
5.4 Future Directions for Research
5.5 Conclusion

Thesis Overview

The accurate forecasting of power system load is essential for the efficient and reliable operation of power systems. This thesis aims to analyze the different techniques and methodologies used for power system load forecasting, with a focus on improving the accuracy and reliability of these forecasts. The study will involve a comprehensive review of the existing literature on load forecasting, including traditional methods and advanced techniques such as machine learning and time series analysis.

The research will also involve the design and implementation of a load forecasting system, which will include data collection, preprocessing, feature extraction, model selection, training, and validation. The performance of the implemented system will be evaluated using real-world data, and comparisons will be made with existing systems. The thesis will conclude with a summary of findings, contributions of the study, implications for power system operations, and future directions for research in the field of power system load forecasting.

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