An experimental test was conducted to compare R245fa with R245fa/R601a on the organic Rankine cycle performance. The major objective of this paper is to ascertain the highest thermal efficiency and the optimal dimensionless volume ratio using the two working fluids. The experimental system consists of an electrically heated boiler, a vapor generator, a scroll expander, a condenser, a working fluid pump, and so on. For the typical weather conditions of May in Tianjin, the experiment results show that the working fluid charge has an important influence on the organic Rankine cycle performances. The optimal isentropic efficiency of the scroll expander corresponds to the design expansion ratio. Underexpanded and overexpanded processes result in the decline of the isentropic efficiency of the scroll expander, with the former playing a major role. R245fa/R601a improves the heat transfer performance in the vapor generator because of the nonisothermal phase change. The highest thermal efficiency for R245fa and R245fa/R601a is 4.38% and 4.45%, thereby illustrating that R245fa/R601a precedes R245fa. The optimal dimensionless volume ratios for R245fa and R245fa/R601a are 0.38 and 0.41, respectively. The experimental test lays foundation of the 500-kW geothermal plant for demonstration in the next step. Copyright © 2014 John Wiley & Sons, Ltd.

This paper reviews the heat transfer model for geothermal reservoirs, the fracture network in reservoirs, and the numerical model of hydraulic fracturing. The first section reviews the heat transfer models, which contain the single-porosity model, the dual-porosity model, and the multi-porosity model; meanwhile the mathematical equations of the porosity model are summarized. Then, this paper introduces the fracture network model in reservoirs and the numerical method of computational heat transfer. In the second section, on the basis of the conventional fracture theory, the PKN (Perkins–Kern–Nordgren) model and KGD (Khristianovic–Geertsma–De Klerk) model are reviewed. Meanwhile, the DFN (discrete fracture network) model, P3D (pseudo-3D) model, and PL3D (planar 3D) model are reviewed. The results show that the stimulated reservoir volume method has advantages in describing the fracture network. However, stimulated reservoir volume methods need more computational resources than conventional fracture methods. The third section reviews the numerical models of hydraulic fracturing, which contains the finite element method (FEM), the discrete element method (DEM), and the boundary element method (BEM). The comparison of these methods shows that the FEM can reduce the computational resources when calculating the fluid flow, heat transfer and fracture propagations in a reservoir. Thus, a mature model for geothermal reservoirs can be developed by coupling the processes of heat transfer, fluid flow and fracture propagation.

Finding the optimal balance between end-user’s comfort, lifestyle preferences and the cost of the heating, ventilation and air conditioning (HVAC) system, which requires intelligent decision making and control. This paper proposes a heating control method for HVAC based on dynamic programming. The method first selects the most suitable modeling approach for the controlled building among three machine learning modeling techniques by means of statistical performance metrics, after which the control of the HVAC system is described as a constrained optimization problem, and the action of the controller is given by solving the optimization problem through dynamic programming. In this paper, the variable ‘thermal energy storage in building’ is introduced to solve the problem that dynamic programming is difficult to obtain the historical state of the building due to the requirement of no aftereffect, while the room temperature and the remaining start hours of the Primary Air Unit are selected to describe the system state through theoretical analysis and trial and error. The results of the TRNSYS/Python co-simulation show that the proposed method can maintain better indoor thermal environment with less energy consumption compared to carefully reviewed expert rules. Compared with expert rule set ‘baseline-20 °C’, which keeps the room temperature at the minimum comfort level, the proposed control algorithm can save energy and reduce emissions by 35.1% with acceptable comfort violation.