Organic Rankine Cycle Systems (ORC) are able to convert efficiently low-temperature geothermal heat sources into mechanical and electrical power or combined heat and power. Especially when producing both heat and power, high operational flexibility is necessary to meet the heat demand and supply electricity in an efficient way. Advanced controllers, as linear quadratic integrators, can be used to guarantee the required flexibility of the ORC unit. Such advanced controllers rely on information on the system state, which is in general non-fully measurable. To reach this goal, state estimators are used and analyzed in this work. First, a dynamic model of an ORC test rig for geothermal application is developed and validated against experimental data, with relative mean squared error for the major variables lower than 1%. Subsequently, a non-linear state estimator for the ORC evaporator coupled with a screw expander is designed and tested on a benchmark case. The considered estimator is an Unscented Kalman Filter based on a finite volume model of the evaporator. The results show that the dynamic and observer model are in good agreement with the experimental data. The observer converges to the wall temperature of the heat exchanger with sufficient accuracy also when starting from a different initial state. The estimated states by the filter can be therefore integrated to advanced single- or multi-variable controllers to maximize the ORC net power output and revenues.     «

Organic Rankine Cycle Systems (ORC) are able to convert efficiently low-temperature geothermal heat sources into mechanical and electrical power or combined heat and power. Especially when producing both heat and power, high operational flexibility is necessary to meet the heat demand and supply electricity in an efficient way. Advanced controllers, as linear quadratic integrators, can be used to guarantee the required flexibility of the ORC unit. Such advanced controllers rely on information on...     »