Advanced monitoring of geothermal Organic Rankine Cycles

Abstract

Geothermal Organic Rankine Cycle (ORC) power plants have tremendous worldwide potential for the utilization of low- and medium-temperature geothermal resources. However, monitoring of such a system is associated with special challenges for plant operators since the generated electrical power fluctuates strongly, which is caused by mainly two reasons: Firstly, due to the changing condensation conditions caused by air-cooled condensers, and secondly, due to the formation of scaling and fouling. Therefore, the process parameters of a geothermal ORC plant are highly variable, both in terms of diurnal and seasonal fluctuations. Considering the currently applied control software in commercial ORC plants, these fluctuations result in challenges regarding a reliable identification of potential degradation processes within the ORC process.This paper presents a novel analytical and data-based methodology for advanced monitoring of the main components of a two-staged subcritical geothermal ORC system in Southern Germany. These components are the heat exchanger, turbine and air-cooled condenser. For this purpose, operational data from more than three years were preprocessed and evaluated.For the shell-and-tube evaporator, this work applies an equation-based simulation model for the calculation of the thermal resistance due to scaling and fouling. For the turbine and condenser, polynomial functions of various degrees and different objective functions for the numerical computation of regression coefficients are examined. Regression models for three years of operation of the investigated geothermal plant were computed and compared with each other.The results indicate that there are no significant negative changes in the operational performance of most ORC main components during the investigated time period. However, negative operational changes are detected over a three-year period for one turbine of the ORC system. The detailed evaluation of the turbine data reveal a decrease of the normalized isentropic efficiency by 10%, which is significantly higher than the calculated RMSE of the developed correlations, thus indicating a clear performance reduction of the turbine. The developed advanced monitoring methodology allows the operator detailed and accurate assessment of the ORC components conditions, which can not be provided by the software solutions of the commercial ORC manufacturer. Furthermore, the presented methodology can also be applied to other thermal cycle systems with similar components, such as the Kalina Cycle.Finally, a user-friendly software application, developed with the MATLAB® App Designer, is presented. The developed software tool facilitates operators to easily and precisely monitor the operation of the main components of a geothermal ORC plant.