Assumption-free modeling of a micro-scale organic Rankine cycle system based on a mass-sensitive method. (1st October 2021)

• Record Type: Journal Article
• Authors: Moradi, Ramin; Habib, Emanuele; Villarini, Mauro; Cioccolanti, Luca
• Is Part Of: Energy conversion and management. Volume 245(2021)
• Publication Date: 2021-10-01
• Subjects: Semi-empirical models -- Off-design conditions -- Mass-sensitive model -- Liquid receiver model -- mass charge distribution; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2021.114554
• Languages: English
• ISSNs: 0196-8904

Abstract

Abstract: Organic Rankine cycle (ORC) systems are one of the most suitable technologies to produce electricity from low-temperature sources. In this paper, the main components of a non-regenerative, micro-scale ORC unit are modeled using the experimental results. These components are then used as functions in the system-level solver developed in MATLAB© to predict the performances of the system at off-design conditions. The proposed system solver is based on a novel approach, in which no assumptions are made about the system's state, and only the components' specifications and the real system boundaries that an operator encounters are adopted as inputs. To this end, the conservation of mass is considered in addition to the conservation of energy in the modeling of the system. Using the assumption-free model, the performances of the ORC system are mapped in the range of the experimental data considering the pump and the expander speeds as variables. The results show that the optimum system net electric performance is achieved at the pump and the expander speeds of 400 rpm and 900 rpm approximately. However, the pump is prone to the risk of cavitation due to low subcooling at the condenser outlet at this condition. Moreover, zero superheating is calculated at the expander suction that is not recommended for its operation. Hence, the developed assumption-free, object-oriented, mass-sensitive model has led to the full understanding of the system limitations and losses in the case of waste heat recovery applications. The proposed approach could be extended also to other ORC systems thus mapping their performances at off-design conditions without making artificial assumptions.