Masterarbeit, 2018
99 Seiten, Note: 4.0
This dissertation aims to determine a cost-effective and reliable hybrid energy system for the Kathmandu University (KU) complex, taking into account the available energy resources and the KU's load demand throughout the year. The study analyzes various energy mix models using HOMER software for cost optimization and RAPTOR software for reliability and availability assessment.
This chapter provides an overview of the study's background, problem statement, objectives, scope, limitations, and significance. It establishes the context for the research and highlights the importance of finding a cost-effective and reliable energy solution for KU.
This chapter reviews relevant literature on energy demand and consumption, renewable energy sources, hybrid energy systems, optimization techniques for hybrid energy systems, and reliability and availability analysis of power systems. It provides a comprehensive understanding of the existing research and theoretical frameworks related to the study's objectives.
This chapter describes the methodology employed in the research, including load profile estimation, energy resource assessment, hybrid energy mix model development, cost analysis using HOMER software, and reliability and availability analysis using RAPTOR software. It outlines the steps taken to collect data, develop models, and analyze the results.
This chapter presents the results of the study, including the load profile analysis, energy resource availability, hybrid energy mix model selection, cost analysis and comparison of models, and reliability and availability analysis of selected models. It analyzes the findings and discusses their implications for achieving a cost-effective and reliable energy system for KU.
The main keywords and focus topics of the dissertation are: cost-effective energy system, hybrid energy mix model, Kathmandu University, HOMER software, RAPTOR software, load profile, renewable energy resources, reliability, availability, cost analysis, optimization, grid, diesel generator, solar PV, batteries, Monte Carlo simulation.
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