Masterarbeit, 2018
99 Seiten, Note: 4.0
Chapter 1
INTRODUCTION
1.1 Background
1.2 Case Study Area
1.3 Statement of Problem
1.4 Research Objectives
1.5 Research Approaches
1.6 Research Nobility
1.7 Scope and Limitations of the Thesis
1.8 Thesis Organization
Chapter 2
LITERATURE REVIEW
2.1 Hybrid Energy Model
2.2 Cost Analysis
2.3 Reliability Analysis
2.4 HOMER software for optimization
2.5 RAPTOR software for Reliability and Availability analysis
2.6 Comparison between On-grid and Off-grid Hybrid System
2.7 Challenges and Issues of Interconnecting Grid and Embedded Generation
Chapter 3
RESEARCH METHODOLOGY
3.1. Problem formulation
3.2. Literature Review
3.3. Input data gathering
3.4. Model Building
3.5. Result Analysis
Chapter 4
RESULTS AND DISCUSSION
4.1 Cost Analysis of Energy Mix Models
4.2 Reliability and Availability analysis of different Energy Mix Models
Chapter 5
CONCLUSION AND RECOMMENDATION
5.1 Conclusion
5.2 Recommendations & Future Work
This study aims to identify the most cost-effective and reliable hybrid energy mix model for the Kathmandu University (KU) complex by evaluating various energy resources, including the grid, diesel generators, and solar PV, under different operational scenarios (on-grid and off-grid) using computational simulation software.
2.3 Reliability Analysis
Reliability studies are important for the system planning, and day to day operating decisions. Reliability analysis of various options is important for the proper selection of standby power systems [3]. Reliability tells us how much failure to expect [9]. Reliability is a measure of the probability that an item will perform its intended or required function or mission for a specified interval under stated conditions [16]. There are two factors used for the measuring the reliability, availability and maintainability of any system. The first factor that demonstrates the reliability is either the Mean Time Between Failure (MTBF) for repairable systems, or Mean Time To Fail (MTTF) for non-repairable systems and the second factor is the failure rate (λ) which is the reciprocal of MTTF or MTBF. So MTBF or MTTF is a direct measure of reliability. More the MTBF or MTTF, more is the reliability. The repair rate (µ) is the reciprocal of Mean Time To Repair (MTTR).
Chapter 1: Provides an introduction to the necessity of reliable power systems in Nepal, defines the research problem within the KU complex, and outlines the research objectives and scope.
Chapter 2: Reviews existing literature regarding hybrid energy models, cost analysis techniques, and reliability evaluation methodologies, including the software used for simulation.
Chapter 3: Details the research methodology, including data collection from the Nepal Electricity Authority, input modeling for HOMER, and the reliability simulation approach using RAPTOR.
Chapter 4: Presents the results of the cost optimization and reliability analysis for the various energy mix models across different operational cases.
Chapter 5: Concludes the study by identifying the most cost-effective and reliable models and provides recommendations for future work, such as power quality studies.
Hybrid Energy Model, Kathmandu University, HOMER, RAPTOR, Monte Carlo Simulation, Cost of Energy, Net Present Cost, Reliability Analysis, Availability, Diesel Generator, Solar PV, Grid Interconnection, MTBF, MTTR, Power Systems.
The dissertation focuses on designing a cost-effective and reliable hybrid energy system for the Kathmandu University complex to mitigate the impact of frequent power outages.
The study evaluates a combination of grid electricity, three different sizes of diesel generators, solar PV, and battery storage systems.
The objective is to identify and compare energy mix models that fulfill the university's load demand while optimizing for levelized cost and system reliability.
The research employs HOMER software for cost optimization and Monte Carlo simulation within RAPTOR software for reliability, availability, and maintainability (RAM) analysis.
The main section covers the systematic building of hybrid models, detailed cost analysis under three different cases, and rigorous reliability simulations to determine the optimal configuration.
Key terms include hybrid energy model, HOMER, RAPTOR, reliability analysis, and total net present cost.
The study shows that the choice of the optimal model shifts significantly depending on whether initial capital investment is included or excluded, as demonstrated by the comparison between Case I and Case III.
Reliability is critical because the university has sensitive loads related to laboratory work, official operations, and presentations that cannot tolerate frequent power interruptions.
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