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A Novel Optimization Algorithm for Reliable Energy based on Wind, Solar and Fuel Cell

Khayyamim, Tara | 2015

1846 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 46957 (55)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Hajsadeghi, Khosro; Zabihollah, Abolghasem
  7. Abstract:
  8. Concerns like fuel cost, pollution and global warming has made it necessary to look for new energy solutions. Renewable and alternative energies have proven themselves to be helpful in this matter. Renewable energy(RE) is the energy that comes from natural resources such as sunlight, wind, rain, tides, waves and geothermal heat, which are naturally replenished at a constant rate. Renewable energies are environmentally friendly, not cheap at the beginning but naturally available in a constant rate and wide spread, unlike fossil fuels that are localized in the limited places. In this thesis in order to generate environmental friendly power we consider two renewable energy resources: wind and photovoltaic, and a clean alternative energy (AE): fuel cells. These two generation sources can be in the form of customized distributed generation (DG) systems in grid connected or standalone structure. In order to have a reliable and cost efficient power generating system, an optimization algorithm based on genetic algorithm is proposed. The proposed system has been tested for different scenarios and has been proven to be a reliable power generating system for various situations
  9. Keywords:
  10. Solar Energy ; Wind Energy ; Genetic Algorithm ; Fuel Cell ; Renewable Energy Resources

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  • Chapter 1:
  • Introduction and Literature Review
    • 1.1. Introduction to Renewable Energy Resources
      • 1.1.1. Solar Power
      • 1.1.2. Wind Power
    • 1.2. Hybridization
      • 1.2.1. Integration Schemes
        • 1.2.1.1. DC-Coupled Systems
        • 1.2.1.2. AC-Coupled Systems
        • 1.2.1.3. Hybrid-Coupled Systems
      • 1.2.2. Unit Sizing and Technology Selection
      • 1.2.3. Storage
      • 1.2.4. Control and Manage Energy
        • 1.2.4.1. Centralized Control Model
        • 1.2.4.2. Distributed Control Model
        • 1.2.4.3. Hybrid Centralized and Distributed Control Model
    • 1.3. Sample Applications
      • 1.3.1. Stand-alone Hybrid Generation combining Solar photovoltaic/Wind turbine and Fuel cell System
      • 1.3.2. Regional integration of renewable energy systems - The role of hybrid energy systems for small communities
      • 1.3.3. Economic evaluation of hybrid renewable energy systems for rural electrification in Iran— a case study
    • 1.4. Conclusion
  • Chapter 2:
  • Modeling Renewable Energy Resources
    • 2.1. PV model
      • 2.1.1. Parameters
      • 2.1.2. Interfaces
      • 2.1.3. Formulation
    • 2.2. Wind Turbine Model
      • 2.2.1. Parameters
      • 2.2.2. Interfaces
      • 2.2.3. Formulation
    • 2.3. Fuel Cell Model
      • 2.3.1. Parameters
      • 2.3.2. Formulation
      • 2.3.3. Dynamics of the cell
    • 2.4. Numerical Example
      • 2.4.1. PV
      • 2.4.2. WT
      • 2.4.3. FC Example
    • 2.5. Conclusion
  • Chapter 3:
  • Optimization Method
    • 3.1. Introduction
    • 3.2. Genetic Algorithm (GA)
    • 3.3. Typical Genetic Algorithm (29)
      • 3.3.1. Initialization
      • 3.3.2. Fitness Evaluation
      • 3.3.3. Selection
        • 3.3.3.1. Roulette wheel selection
        • 3.3.3.2. Tournament selection
      • 3.3.4. Crossover
        • 3.3.4.1. Single-point crossover
        • 3.3.4.2. Multiple-point crossover
      • 3.3.5. Mutation
    • 3.4. My Algorithm
      • 3.4.1. Initialization
      • 3.4.2. Diversity Control
      • 3.4.3. Scaling
      • 3.4.4. Selection
      • 3.4.5. Death
      • 3.4.6. Fitness Evaluation
      • 3.4.7. Elitism
      • 3.4.8. Random Search
      • 3.4.9. Trim GA
    • 3.1.
    • 3.5. Proposed Algorithm
    • 3.6. Fuel Cell Parameters Optimization
  • Chapter 4:
  • Scenarios and Optimization Results
    • 4.1. Economic analysis
      • 4.1.1. Formulation
      • 4.1.2. PV Costs
      • 4.1.3. WT Costs
      • 4.1.4. FC Costs
    • 4.2. Scenario 1
      • 4.2.1. Solar
      • 4.2.2. Wind
      • 4.2.3. Solar and Wind
      • 4.2.4. Solar, Wind and Fuel Cell
    • 4.3. Scenario 2
    • 4.4. Scenario 3
    • 4.5. Conclusion and Future Work
  • References
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