DEVELOPMENT OF AN OPTIMIZATION FRAMEWORK FOR MICRO-GRID ENERGY CONVERSION SYSTEMS

A comprehensive optimization study considering both system configurations and control strategies is needed for micro grid energy systems. In order to address this need, this study provides an advanced optimization framework that extends existing energy system optimization studies in following four aspects: complete system optimization from scratch; comprehensive energy conversion equipment modeling for heating, cooling and power generations; modeling of cascaded configurations such as a cascaded absorption-compression refrigeration system and a cascaded organic Rankine cycle-direct heating system; and consideration of transient loads and weather profiles. The optimization framework aims to find optimum system configurations and control strategies for any given equipment options, and load- and weather-profiles in order to minimize life cycle cost. First, correlation based equipment models and cascaded system models were developed. Then the optimization framework was established using a genetic algorithm solver built in Matlab. The framework was presented through a case study on an oceanic container transportation application under transient loads and weather profiles. It was found that the optimized system was able to reduce life cycle cost by 40%. The optimized system is in favor of cascaded organic Exploring waste heat from the main engine that is used for main propulsion is the key to reduce life cycle cost. The developed optimization framework can be used for any applications as an efficient tool to search for novel energy system designs and their evaluations.