| Summary: | 碩士 === 國立臺北科技大學 === 化學工程與生物科技系化學工程碩士班 === 107 === Hybrid power systems (HPSs) are a major application of distributed generation, defined as utilizing two or more conventional and renewable energy resources for power generation. HPSs are thus more efficient than single-resource systems. The availability and power output of renewable energy (RE) resources depend on local weather conditions and have stochastic characteristics. Integrating complementary RE resources and deploying energy storage or backup energy devices are thus common strategies to improve the system reliability. Solar PV and wind power with battery storage form a promising option of HPS applications.
This thesis presents a mathematical model for optimal HPS design. Chance-constrained programming is incorporated to account for uncertainties in power resources and load demands, and the reliability requirement of power supply. Furthermore, fuzzy optimization is used to address conflicting design objectives, as increasing the use of RE in the HPSs reduces the associated carbon emissions but increases the total cost.
Among the Pareto optimal solutions, the fuzzy model provides compromise solutions with the trade-off between economic and environmental goals. The results obtained from the chance-constrained programming approach are then verified using Monte Carlo simulation. Parameter uncertainties, in cost and emission factors are also allowed for, resulting in more conservative solutions. Two case studies are presented to illustrate the proposed approach.
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