(91a) Multi-Objective Optimization for Optimal ORC(organic Rankine cycle) Design Considering Inherent Risk, Exergy Efficiency
Inherent safety is technique for designing safer process, which minimize risk of process. This technique give insight about process risk and strategies for reduction of risk in early stages of process design. Most of all, if there are some risky points in the process design, the design can be changed cost-effectively due to characteristics in early stages of design. However, research for inherent safety still need complicate progress and depends on subjective judgment due to lack of a standard measurement method. In addition, risk reduction is applied to complete process design in specific design stages. After risk reduction, if severe decrease of energy efficiency happen, improvement of design is necessary again. Then inherent safety technique will be applied again, and these steps may be repeated. Therefore, decision method is needed, which decides between risk and energy efficiency for proper design. Organic Rankine cycle(ORC), which use organic working fluid, is sustainable energy utilization technology by converting low temperature(low quality) heat to electricity. Exergy efficiency, which means available work or availability, is the best parameter to measure performance of ORC. Exergy efficiency of ORC depends on a sting of variables, which operating pressure, kinds of heat source and so on. Most of them, kinds of working fluids and their composition are effective parameters. And its structure and working condition are effective parameters as well. In this study, inherent safety technique, which contains decision method between risk and efficiency, is proposed and applied to ORC process. The ORC uses liquefied natural gas(LNG) as cold exergy source, which is not utilized in general. Proposed method is considering risk(or safety) and efficiency(or process) simultaneously by solving optimization problem. As a result, multi-objective optimization method is used for optimal design considering safety aspect and process aspect. Optimization variables include working conditions(pressure, temperature), working fluid conditions(composition) and ORC structure ORC. In conclusion, Pareto-optimal solutions are obtained and best optimal solution is selected by decision technique.