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Title: Optimization of wind-solar energy systems using low wind speed turbines to improve rural electrification
Author: Sangpanich, Umarin
ISNI:       0000 0004 2744 7419
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2013
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Electricity is significant in improving the quality of life for people in rural and remote areas in developing countries. There are two main options for Rural Electrification (RE), namely grid extension and stand-alone systems. The governments and developers face the challenges of their limitations, namely technical, economic and environmental effects of each RE choice. This thesis intends to improve RE by focusing on renewable energy technologies, namely Wind Turbine (WT) and Photovoltaic (PV) systems. They have been developed and applied to RE because they are simple and environmentally friendly. They can be installed as separate units and they are sustainable alternative energy solutions. Installation, cost and performance are crucial issues of WT and PV applications, and are based on the terrain and climate where the renewable are installed. The efficiency of WTs and PV modules has increased, while their cost has declined continuously. However, a PV system still has installatio n costs around two times more expensive per watt than WTs. Most WTs using current technology can be financially worthwhile for high wind speed areas, having wind speeds greater than 6.4 m/s at 10 m hub height, but most rural areas have wind speeds of less than 6 m/s at the same height. Therefore, Low Wind Speed Turbines (LWSTs) have evolved, by increasing rotor diameter and while maintaining similar generator capacity. This is to reduce Levelized Cost of Energy (LCOE) for WTs in low wind speed areas. This thesis proposes simple cost models, namely the Sum-component cost model and the Total-cost model in order to calculate the LCOE of LWSTs. In addition, novel aspects of this thesis are that the optimization processes of stand-alone hybrid WT-PV systems and hybrid WT-PV systems using batteries at peak demand in remote area power systems provide simple, fast and flexible methods, by applying Multi-objective Evolutionary Algorithm (MOEA). The MOEA can analyze complex objective problems a nd provide an accurate multi-objective method. Results from relevant case studies show that the cost models and the optimization processes proposed are novel and are valuable tools for analysis and design, including the approaches for improving the system reliability and for estimating the Initial Capital Cost (ICC) of WTs having different rated wind speeds. The proposed algorithms are generic and can be utilized for other energy planning problems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available