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This article deals with a thermal energy storage system in the form of a water tank with a thermocline. The well-known thermocline phenomenon is modeled using computational fluid dynamics (CFD). However, the reservoir model proposed in this article is zero-dimensional. This is due to the fact that the aim of this article is to build a mathematical model that will be more useful in mathematical models of complex energy systems in which a hot water tank is one of many elements of the system. In such a zero-dimensional mathematical model, the hot water tank will be modeled using equations describing heat transfer, and the thermocline itself will be treated as a heat transfer surface with known dimensions and heat transfer coefficient. A novelty of this paper is that it addresses heat loss across the thermocline as defined in this manner. A CFD model of a thermal storage tank is created, validated with available experimental data, and used to obtain the heat transfer coefficient U. The resulting value is then analyzed quantitatively and qualitatively and the changes in the thickness of the thermocline are accounted for in the equation. The results from this groundbreaking work can be used to analyze heat storage in the form of thermocline water tanks at the level of system modeling, e.g., for the purpose of configuring the structure of other devices and control systems. [ABSTRACT FROM AUTHOR]

Summary: Growing installed capacity in renewable energy sources is driving demand for energy storage in the power systems. Compressed air energy storage (CAES) technology can provide a good alternative to pumped energy storage, with high reliability and good efficiency in terms of performance. The article presents three constant volume CAES systems: (i) without recuperation, (ii) with recuperation, and (iii) adiabatic. Dynamic mathematical models of these systems were built using Aspen HYSYS software. Adiabatic compressed air energy storage system with liquid thermal energy storage achieved round trip efficiency of 64.8%. [ABSTRACT FROM AUTHOR]

The paper presents a thermodynamic analysis of selected CAES and LAES systems. The LAES cycle is a combination of an air liquefaction cycle and a gas turbine power generation cycle. CAES and LAES systems are simulated using Aspen HYSYS software. CAES is modeled in a dynamic mode. A comprehensive thermodynamic analysis was conducted along with the comparison of storage volumes. The results indicate that both systems are characterized by high energy storage efficiency, equal to approximately 40% for the CAES and 55% for the LAES systems. One clear advantage of the LAES over the CAES is the significantly lower volume demanded for energy storage. For the considered LAES system,the liquid air tank volume is around 5000 m 3 , while for the CAES the cavern volume is approximately 310000 m 3 . Heat exchangers and combustion chambers are the main contributors to the total exergy destruction in the analyzed systems. [ABSTRACT FROM AUTHOR]

The paper presents a thermodynamic analysis of a selected hypothetical liquid air energy storage (LAES) system. The adiabatic LAES cycle is a combination of an air liquefaction cycle and a gas turbine power generation cycle without fuel combustion. In such a system, heat of compression is stored and subsequently used during the expansion process in the turbine. A mathematical model of the adiabatic LAES system was constructed. Balance calculation for a selected configuration of the energy storage system was performed. The influence of pressure in the air liquefaction cycle and the gas turbine power generation cycle on storage energy efficiency was analyzed. The results show that adiabatic liquid air energy storage systems could be very effective systems for storing electrical power, with efficiency levels reaching as high as 57%. [ABSTRACT FROM AUTHOR]

The article shows the proposed solution of the objective function for the seasonal thermal energy storage system. In order to develop this function the technological and economic assumptions were used. In order to select the optimal system configuration mathematical models of the main elements of the system were built. Using these models, and based on the selected design point, the simulation of the entire system for randomly generated outside temperatures was made. The proposed methodology and obtained relationships can be readily used for control purposes, constituting model predicted control (MPC). [ABSTRACT FROM AUTHOR]