1. LNG cold energy can be used to generate electricity through an Organic Rankine Cycle (ORC).
2. The power output increases with the number of stages, but complexity, cost, maintenance intensity and risk of failure also increase.
3. Simulations show that a two-stage ORC with the first stage in series is the best compromise between complexity and power output, reducing power output by 8.6% compared to a three-stage system but providing a 20% reduction in heat exchanger surface area.
The article provides an overview of how LNG cold energy can be used to generate electricity through an Organic Rankine Cycle (ORC). It discusses the trade-off between complexity and power output when using different numbers of stages for the ORC system, and presents simulations showing that a two-stage ORC with the first stage in series is the best compromise between complexity and power output.
The article appears to be well researched and reliable, as it provides detailed information on how different configurations of ORC systems affect power output and complexity. The simulations presented are based on real data from sea water as a heat source, ethylene, ethane and propane as working fluids, and given total heat exchanger surface area. The article also provides clear conclusions about which configuration is most suitable for practical implementation.
However, there are some potential biases in the article that should be noted. For example, it does not discuss any possible risks associated with using LNG cold energy or ORCs in general; nor does it explore any counterarguments or present both sides equally when discussing the trade-off between complexity and power output. Additionally, while it does provide some detail on how different configurations affect power output and complexity, it does not provide any evidence for its claims or explore other points of consideration such as cost or maintenance requirements for each configuration.
In conclusion, while this article appears to be well researched and reliable overall, there are some potential biases that should be noted when considering its trustworthiness and reliability.