Cloud Based Simulation of ORC Systems

orc2019 Tracking Number 185

With the increasing interest in ORC systems, accurate thermodynamic models of the ORC systems and their integration with other systems such as geothermal plants, biomass combustion and gasification plants, solar power plants or industrial processes are of great value. They provide insight into the process details and can be used to optimize the performance of the system. However, to create such models in a traditional way, substantial locally installed resources are required. If a project is developed in a collaborative effort, the resources need to be replicated for each partner. Cloud based systems are changing the work flow in many areas and make collaboration easier and more efficiency. This paper describes a flexible cloud-based simulation platform for ORC processes, making simulation easier accessible than traditional solutions and offering options for new ways to work on projects. The platform presented allows to create, configure and solve ORC process models in the cloud. All interaction with the model, from defining the model to reporting results, is done via a web browser. It is not necessary to install any software locally. Taking advantage of recent developments in browser technology, in particular HTML5, a browser-based user interface has been developed. It can be used with the current versions of any of the major web browsers. The user interface allows to set up and configure the process model graphically based on predefined component. It is used to specify process parameters and to display simulation results. In this way, the system represents a complete Software as a Service (SaaS) solution. The underlying architecture of the system is presented. The paper presents results obtained for various examples of ORC processes. It explains the capabilities of the platform and discusses benefits and risks of the cloud-based approach. The work presented has been developed with partial funding received from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº685793