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08:40   Session 15: Modelling and simulation
Chair: Christos Markides
20 mins
Adrian Rettig, Ulf Christian Müller
Abstract: Converting industrial waste heat to electricity using organic ranking cycle (ORC) technology is an effective method to improve energy efficiency and reduce cost. However, the waste heat source is often characterized by relatively large fluctuations in load making it a demanding task to design and operate an ORC in an efficient and economically sound manner. Compounding this challenge are the relatively tight profit margins of ORC projects in general even with the support of governmental subsidies along with the tendency to use only a rough estimation in predicting performance. These factors increase the uncertainty when trying to create an economically successful operation. To build the business case on a firm foundation, performance prediction that takes into consideration all relevant operation aspects is inevitable. Therefore a reliable performance prediction tool for the use in an early project phase is highly desired and has been developed in this project. The performance prediction tool uses Modelica as the modeling platform and is comprised of the ThermoCycle library [1] in combination with the CoolProp software [2] necessary for calculating fluid properties. Whereas the ThermoCycle library provides robust and computationally efficient generic models for many ORC components, a newly developed library deals with the dynamic transient modeling of industrial plants in operation that contain an ORC. Specifically, two ORC applications in Switzerland have been investigated and used for parameterization and calibration: a large scale application in the cement industry and a small bio gas CHP application. The investigated plants show significant operating hours in the part load regime with many automatic shut-down and start-up cycles due to external limiting conditions such as high ambient temperatures or low engine output power. With the implemented transient models and the deduced control strategies, the measured ORC power output well predicts the industrial behavior over a longer period of time. This shows the approach to be a viable method to allow future performance prediction with a higher certainty. In addition, the dynamic models of the overall plants may be used to support future tasks necessary during the whole life cycle of an ORC plant (e.g. determining optimal control strategy concepts, pre-tuning of control parameters, troubleshooting during commissioning, planning service intervals etc.). Assessing additional ORC industrial applications will extend and boost the prediction capabilities of the tool, contributing to an ecological and efficient use of energy. [1] S. Quoilin, A. Desideri, J. Wronski, I. Bell, V. Lemort. ThermoCycle: A Modelica library for the simulation of thermodynamic systems, Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden [2] I. Bell, J. Wronski, S. Quoilin, and V. Lemort. Pure and Pseudo-pure Fluid Thermophysical Property Evaluation and the Open-Source Thermophysical Property Library CoolProp, Industrial & Engineering Chemistry Research 2014 53 (6), 2498-2508
20 mins
Adriano Desideri, Jorrit Wronski, Bertrand Dechesne, Martijn van den Broek, Gusev Sergei, Sylvain Quoilin, Vincent Lemort
Abstract: Dynamic modeling has assumed an important role in energy system design, in particular when control issues are considered. In the last years, new methodologies for dynamic modeling have been developed and implemented in various dynamic modeling languages, such as the open-access Modelica language. When considering low capacity energy systems such as an ORC system, the governing dynamics is mainly concentrated in the heat exchangers. As a consequence, accuracy and simulation speed of a "high-level" model mainly depend on the heat exchanger models. In particular, heat exchangers models capable of handling phase changes are required for thermodynamic cycles presenting evaporation or condensation. To that aim, the two usual approaches are the finite-volume (FV) and moving boundary (MB) methods. This paper presents a MB model developed in the framework of the open-source ThermoCycle Modelica library. A comparison of this model with the more traditional FV approach is performed in terms of simulation speed, robustness and accuracy. The stability and integrity of the models are demonstrated as single components and within a complete ORC system model. The moving boundary model has been formulated in a way that allows switching between different configurations, i.e. general, flooded and dry evaporators and condensers, and it results to be very effective in terms of simulation speed and accuracy compared with the finite volume model.
20 mins
Davide Ziviani, Brandon Woodland, Emeline Georges, Eckhard Groll, James Braun, Travis Horton, Michel De Paepe, Martijn van den Broek
Abstract: An increasing interest in organic Rankine cycle (ORC) technology has led to numerous simulation and optimization studies. In the open-literature different modeling approaches can be found, but general software tools available to the academic/industrial community are limited. A generalized ORC simulation tool, named ORCSim, is proposed in this paper. The framework is developed using object-oriented programming that easily allows improvements and future extensions. Currently two cycle configurations are implemented, i.e. a basic ORC and an ORC with liquid-flooded expansion. The software architecture, the thermo-physical property wrappers, the component library and the solution algorithm are discussed with particular emphasis on the ORC with liquid-flooded expansion. A thorough validation both at component and cycle levels is proposed by considering the aforementioned cycle architectures.
20 mins
Rémi Dickes, Olivier Dumont, Arnaud Legros, Sylvain Quoilin, Vincent Lemort
Abstract: Simulations of organic Rankine cycles and their components can be performed by many types of modeling tools which are characterized by their own level of details. From empirical laws to deterministic methods via semi-empirical models, different modeling complexities can be chosen to simulate a given system. Beside of the predicted performance, the level of details impacts the simulation speed and its robustness. The more deterministic the method, the more complicated the model development and the more computationally intensive the simulation. There are many applications for which deterministic and complex models cannot be implemented. For example, if the ORC is integrated in a larger system, such as a solar power plant [1], the simulation speed and robustness can be critical if all the components of the system, including the ORC, are modeled in details. Therefore it is substantial to evaluate the prediction error committed when using simplified approaches to evaluate the system performance in off-design operating conditions. In this work, simulation results of an ORC unit predicted by models of different levels of complexity (i.e. deterministic, semi-empirical and empirical approaches) are analyzed. A 3kWe ORC test bench is chosen as study case and experimental data are used for reference. The system consists of two plate heat exchangers, a scroll expander, a volumetric pump and an air-cooled condenser. In this paper, the components of the test bench are modeled using different approaches of increasing complexity and each model is calibrated using experimental data from the test rig. The goodness of fit as well as the benefits and limitations of each modeling methods are analyzed and discussed.
20 mins
Angelo La Seta, Jesper Graa Andreasen, Leonardo Pierobon, Giacomo Persico, Fredrik Haglind
Abstract: Organic Rankine cycle power systems have recently emerged as promising solutions for waste heat recovery in low- and medium-size power plants. Their performance and economic feasibility strongly depend on the expander. Its design process and efficiency estimation are particularly challenging due to the peculiar physical properties of the working fluid and the gasdynamic phenomena occurring in the machine. Unlike steam Rankine and Brayton engines, organic Rankine cycle expanders have to deal with small enthalpy drops and large expansion ratios. These features yield turbine designs with few highly-loaded stages in supersonic flow regimes. This paper proposes a design method where the conventional cycle analysis is combined with calculations of the maximum expander performance using a validated mean-line design tool. The high computational cost of the turbine optimization is tackled building a model which gives the optimal preliminary design of the turbine as a function of the cycle conditions. This allows to estimate the optimal expander performance for each operating condition of interest. The test case is the preliminary design of an organic Rankine cycle turbogenerator to increase the overall energy efficiency of an offshore platform. The analysis of the results obtained using a constant turbine efficiency and the method proposed in this paper indicates a maximum reduction of the expander performance of 10 %−points for pressure ratios between 10 and 35. This work also demonstrates that this approach can support the plant designer on deciding the optimal size of the organic Rankine cycle unit when multiple exhaust gas streams are available.