| Clean water is essential, but electricity is also very important. It fosters technological innovations, scientific discoveries and better living conditions. Access to electricity is a prerequisite for poverty eradication and economic development for developing countries. However, there are regions in the world where people do not have access to the power utility. In addition, as the price of oil continues to rise and many energy experts predicting this type of energy source will not sustain our energy consumption in the future, fossil energy in general becomes an economically unstable source of electricity. On the other hand, global demand for electricity keeps increasing and so alternative sources of electricity must be considered to meet our energy demand.;The move toward sustainable and renewable energy is evident with the available commercial renewable energy technologies. The U.S. Department of Energy has developed a roadmap that envisions widespread deployment of renewable energy sources by 2020 in order to strengthen our energy security in the future. However, there are a set of challenges associated with renewable energy sources due to their intermittent and non-dispatchable characteristics. Studies have shown that incorporating the use of energy storage with renewable energy improves the cost effectiveness, reliability, power quality, and efficiency of the power system. But determining the optimal mix of power generation sources for this hybrid power system and how to optimally allocate the power/energy flow become an interesting Operations Research (OR) problem. We call this problem a Hybrid Power System Design Problem (HPSDP).;The problem considered in this dissertation is to identify optimal power generation combining the utilization of renewable energy sources and non-renewable sources to minimize the total power generation life-cycle cost of the renewable project. In this dissertation, we present a system modeling approach to perform analysis and optimization of hybrid power system.;The contributions of this research include: (1) the development of a methodology to represent the non-closed form life-cycle cost model of the power system components as a piece-wise linear cost function to be used in the optimization model, (2) the development of a Mixed Integer Programming (MIP) model of the HPSDP, (3) the development of heuristic algorithms that can provide optimal or near-optimal solutions to the HPSDP more efficiently compared to the exact method of solving the MIP using a commercial solver such as CPLEX, (4) the development of a solution methodology that combines statistical analysis technique with a cost-dominant search procedure to reduce computation time while maintaining the same solution quality compared to the methodology implemented by a widely used HPSDP software (HOMER), and (5) the development of a mathematical programming solution approach using the robust optimization concept to address the stochastic variant of the HPSDP. |
