The Thermo‐Economic Potential of ORC‐Based Pumped‐Thermal Electricity Storage: Insights from the Integrated Design of Processes and Working Fluids

Abstract

Higher shares of renewable energy increase the need for electricity storage. A promising storage technology is Pumped‐Thermal Electricity Storage (PTES): PTES systems transform electricity into heat using a heat pump (HP) and reconvert the heat into electricity using a heat engine. Since both HPs and heat engines require working fluids, maximum performance requires the optimal combination of PTES process and working fluids. Herein this work, the thermo‐economic potential of an Organic Rankine Cycle (ORC)‐based PTES system is analyzed by simultaneously designing both the PTES process and the working fluids used in the HP and the ORC. To rigorously explore the molecular design space, the 1‐stage Continuous‐Molecular Targeting ‐ Computer‐Aided Molecular Design method is employed. Detailed models for costing and sizing of the equipment allow for a thermo‐economic design of the PTES. The computer‐aided molecular design formulation integrates the working fluids as degrees of freedom into the process optimization. For the investigated ORC‐based PTES system with an input power of 60 MW, the optimal process and working fluids minimize the specific investment cost to SIC = 929 € kWh out − 1 . The analysis of cost drivers shows that with decreasing compressor cost, the investigated ORC‐based PTES system can become a competitive storage technology.

Refrigerant Selection for Heat Pumps: The Compressor Makes the Difference

“…In the past, 1-stage CoMT-CAMD has been applied to organic Rankine cycles, [13,14,33] to physical CO 2 absorption processes, [34] and to pumped-thermal electricity storage systems. [24] In this Table 2. Compressor parameters for refrigerant-dependent compressor model.…”

“…In the past, 1‐stage CoMT‐CAMD has been applied to organic Rankine cycles, [ 13,14,33 ] to physical absorption processes, [ 34 ] and to pumped‐thermal electricity storage systems. [ 24 ] In this work, the integrated design of heat pump and refrigerant is addressed, leading to the following mixed‐integer nonlinear optimization problem (MINLP) …”

“…As a consequence, the studies either neglect compressor losses [7,[19][20][21] or model the compressor with an isentropic efficiency identical for all refrigerants. [9,[22][23][24] Other studies introduce process and refrigerant dependency using empirical correlations for the isentropic efficiency. [7,20,25] However, these empirical correlations are fit to data for only a few refrigerants, and refrigerant extrapolation is neither guaranteed nor proven.…”

Energy, exergy, economic, and environmental (4E) analysis of a pumped thermal energy storage system for trigeneration in buildings

“…The total electricity input (P el,in ) to the system consists of the electricity consumption of the 3 compressors and is described using the following equation: P e1,in = P e1,1 + P e1,2 + P e1,3 (11) In addition, the ORC is described using the following equations. First of all, the heat input in the ORC (Q ORC ), which is the same as the high-temperature thermal load (Q high ) because no energy gains or losses occur, can also be described as follows:…”

“…This decrease could lead to higher ORC power production. According to the results, the ORC electricity production increased by 15.3% to 41.5% for the case of using the absorption refrigeration cycle, while the round-trip efficiency and the levelized cost of storage also increased and were found to be 142%, and 0.242 $ per kW per h. Finally, Tillmanns et al 11 studied a PTES configuration thermo-economically, which included a heat pump and an ORC. To optimize the system in terms of its properties and working media, the authors developed the 1-stage Continuous-Molecular Targeting – Computer-Aided Molecular Design method.…”