Thermal Energy Storage Model Research Articles

Development & Validation of a Packed Bed Thermal Energy Storage Model

The rapid growth of economies and population around the world have exponentially increased the demand for energy. This demand has invoked increased annual global CO2 emissions and necessitated a transition to clean energy technologies. Reliable and affordable energy storage technologies are paramount for increasing renewable energy penetration onto the grid, supporting periods with reduced or no renewable energy generation. This project is aimed at developing a Thermal Energy Storage (TES) solution that can deliver heat to a heat engine for power production or to an industrial process for prolonged periods. TES long duration energy storage (LDES) presents many potential benefits, including 1) Low Cost 2) scalability 3) high energy density 4) low carbon footprint and 5) resiliency via ability to produce synchronous power (i.e., spinning turbomachinery). The broader objective of this project is to build, test, and model the TES concept at a 2 MWh scale to determine the economic and physics-based practicality of the system. The work presented here describes the first phase objectives of the project, including benchtop scale testing, model development, and Model Validation.

Development of a Thermal Energy Storage Model for Performance Prediction of Heat Pump Systems Linked with Multiple Heat Sources

Development of a Thermal Energy Storage Model for Performance Prediction of Heat Pump Systems Linked with Multiple Heat Sources

Development, validation and demonstration of a new Modelica pit thermal energy storage model for system simulation and optimization

Space heating applications account for a high share of global greenhouse gas emissions. To increase the renewable share of heat generation, seasonal thermal energy storage (STES) can be used to make thermal energy from fluctuating renewable sources available in times of high demand. A popular STES technology is pit thermal energy storage (PTES), where heat is stored underground, using water as a storage medium. To evaluate the use of PTES in an energy system, easily adaptable, publicly accessible and tool independent models are needed. In this paper, we improve an existing PTES model developed in the Modelica modeling language. The model is cross-compared with a more detailed and previously validated COMSOL model, considering different amounts of insulation, showing a deviation of 2–13% in the observed annual charged and discharged amount of heat. The results indicate that the presented model is well suited for early design stage and an exemplary case study is performed to demonstrate its applicability in a system context. Dimensions of system components are optimized for the levelized cost of heat (LCOH), both with and without subsidies, highlighting the importance of subsidies for the transition towards climate friendly heating solutions, as the gas boiler use is reduced from 47.6% to 2.7%.

Multi-factor analysis and optimization design of a cascaded packed-bed thermal storage system coupled with adiabatic compressed air energy storage

In an adiabatic compressed air energy storage (A-CAES), one of the key components is the heat storage system, in which the packed bed filled with encapsulated phase-change capsules has been widely investigated because of its excellent thermal performance. In this paper, a packed-bed thermal energy storage model with three layers of phase change materials (PCM) is proposed in the context of an A-CAES. Four factors primarily affecting the thermal performance of the packed bed thermal storage system, namely the mass flow rate of heat transfer fluid (HTF), the inlet temperature of HTF, the cascade situation of PCM, and the arrangement of particle sizes, are critically analyzed by conducing the orthogonal experiments. On this basis, the machine learning method is applied to predict and optimize the thermal performance of the packed bed aiming to find the optimal results. The comparison of results between the optimized and original models expressively shows a reduction of 8.46% in PCM mass, an increase of 92.18%/116.82% in the overall heat storage/release quantity, and an increase of 19.23% in the overall efficiency. This work outlooks a guideline for the potential application of packed bed in A-CAES.

Stratified thermal energy storage model with constant layer volume for predictive control — Formulation, comparison, and empirical validation

Recent developments in heating systems have witnessed a significant increase of heat pumps with a highly temperature-dependent efficiency. Optimal real-time operation of these heating systems with predictive control requires a thorough understanding and modeling of the internal temperature distribution of the associated thermal energy storage. At the same time, the thermal energy storage models need to be sufficiently simple to ensure computational tractability in real-time predictive control. Therefore, this article presents a stratified thermal energy storage model with constant layer volume and variable temperature suitable for real-time predictive control. The model employs a novel formulation with quadratic or simpler constraints which enable high accuracy at low computation burden. The proposed model is validated experimentally and compared with other models available in literature. The results show that the proposed stratified thermal energy storage model represents the real-world behavior of a thermal energy storage with great accuracy, while reducing the required computational burden as compared to other models for real-time operation and control. A case study further demonstrates that the increased accuracy of the proposed new model leads to cost and energy savings for the operator.

Comprehensive analytical model of energy and exergy performance of the thermal energy storage

Determining the performance of heat storage units is essential to reliably determine the capability of entire energy storage systems, as several energy loss and dissipation phenomena can significantly degrade its final efficiency. Previous scientific works has not focused on the detailed treatment of the heat storage tank and its impact on the functioning of other system components. The work emphasizes the presentation of a in-house numerical model of Thermal Energy Storage filled with rock material. The comprehensive numerical model has been presented that also takes into account the variable operating parameters of the compressor and air expander. The multivariate nature of the model used makes it possible to estimate the influence of individual factors on the final efficiency of the system. The calculations made it possible to determine the potential of a system with a capacity of 175 MWh using post-mining shafts. The long-term energy efficiency of the system was 57.47%, with a heat storage energy efficiency of 91.96% and an exergy efficiency of 82.93%. Implementation of the model has the potential to provide more accurate estimations of the potential of proposed energy systems using heat storage.

Provision of multiple services with controllable loads as multi-area thermal energy storage

Power systems are experiencing a decrease of synchronous generation along with increased penetration of inverter based renewable generation leading to reduced system inertia and a need for flexible resources. Non-generating resources such as thermostatically controlled loads (TCLs) are flexible due to their thermal energy storage capacity. When aggregated, TCLs can arbitrage energy prices and provide reserves to the power system. We approach the operational flexibility of the TCLs by modeling a risk-averse aggregator that controls decentralized TCLs and aims to maximize its own profit. The high number and low power rating of residential TCLs makes it difficult to model and assess their flexibility potential on national level. Thus, we make use of a high-level thermal energy storage model for aggregations of TCLs to quantify their flexibility potential. We present a method to aggregate temperature, TCL parameters, and building stock data into a thermal battery equivalent. We propose a multi-period multi-market multi-zonal two-stage chance constrained rolling horizon optimization problem formulation for the risk-averse day-ahead self-scheduling problem of a price-taker TCL aggregator bidding in energy and reserve markets under uncertainty and recast the problem as a linear program. We perform several case studies in the Swedish power system based on a survey of single- and two-family dwellings with electric heating and assess the flexibility potential. Additionally, a sensitivity analysis provides insights regarding market design and policy implications.

Component-based modeling of ground-coupled seasonal thermal energy storages

Seasonal thermal energy storages are considered a central element of modern, innovative energy systems and help to harmonize fluctuating energy sources. Furthermore, they allow for an improved coupling between the electricity and heating sectors. Despite recent improvements of planning processes and enhanced models, significant discrepancies between projected and measured heat losses were revealed. Additional shortcomings of available tools relate to limitations in specifying geometry, internal design, or physical processes. Addressing these drawbacks, this study employs a revised, alternative approach by using a flexible, component-based, model (“STORE”). It allows variable flexible parameterizations to study diverse design scenarios. After introducing relevant seasonal thermal energy storage components, processes and mechanisms, datasets, and evaluation techniques, a plausibility test is presented that applies a common thermal energy storage model for benchmarking. In a test study, the re-use of a circa 1,000 m3 large swimming pool is simulated. STORE is used to investigate performance trends caused by different designs (e.g., insulation thicknesses, materials at individual interfaces). For the plausibility test, the results show a high degree of coverage and good applicability. Further, the results of the test study show a storage efficiency of 12.4% for an uninsulated base case, which can be improved to 69.5% in case of the most complex, highly insulated configuration. Critical trends are revealed, covering reduced peak capacity levels (26.5 to 23.5 MWh) and raised average filling temperatures (39.1 to 45.2 °C). Improved long-term behavior involves reduced environmental impacts due to reduced heating of the ambient soil (+7.9 K compared to +14.1 K after 2 years). General conclusions reveal that an optimal design should initially focus on an external cover of soil and top insulation. However, evaluations should base on multiple parameters depending on the target criteria. This is where the present model is highly useful. The capability of STORE to rapidly analyze a plethora of scenarios proves its high applicability for optimizing the planning processes of seasonal thermal energy storage projects.

Non-Stoichiometric Redox Thermochemical Energy Storage Analysis for High Temperature Applications

Concentrated solar power is capable of providing high-temperature process streams to different applications. One promising application is the high-temperature electrolysis process demanding steam and air above 800 °C. To overcome the intermittence of solar energy, energy storage is required. Currently, thermal energy at such temperatures can be stored predominately as sensible heat in packed beds. However, such storage suffers from a loss of usable storage capacity after several cycles. To improve such storage, a one-dimensional packed bed thermal energy storage model using air as a heat transfer medium is set up and used to investigate and quantify the benefit of the incorporation of different thermochemical materials from the class of perovskites. Perovskites undergo a non-stoichiometric reaction extension which offers the utilization of thermochemical heat over a larger temperature range. Three different perovskites were considered: SrFeO3, CaMnO3 and Ca0.8Sr0.2MnO3. In total, 15 vol% of sensible energy storage has been replaced by one perovskite and different positions of the reactive material are analyzed. The effect of reactive heat on storage performance and thermal degradation over 15 consecutive charging and discharging cycles is studied. Based on the selected variation and reactive material, storage capacity and useful energy capacity are increased. The partial replacement close to the cold inlet/outlet of the storage system can increase the overall storage capacity by 10.42%. To fully utilize the advantages of thermochemical material, suitable operation conditions and a fitting placement of the material are vital.

A Hybrid Bimodal LSTM Architecture for Cascading Thermal Energy Storage Modelling

Modelling of thermal energy storage (TES) systems is a complex process that requires the development of sophisticated computational tools for numerical simulation and optimization. Until recently, most modelling approaches relied on analytical methods based on equations of the physical processes that govern TES systems’ operations, producing high-accuracy and interpretable results. The present study tackles the problem of modelling the temperature dynamics of a TES plant by exploring the advantages and limitations of an alternative data-driven approach. A hybrid bimodal LSTM (H2M-LSTM) architecture is proposed to model the temperature dynamics of different TES components, by utilizing multiple temperature readings in both forward and bidirectional fashion for fine-tuning the predictions. Initially, a selection of methods was employed to model the temperature dynamics of individual components of the TES system. Subsequently, a novel cascading modelling framework was realised to provide an integrated holistic modelling solution that takes into account the results of the individual modelling components. The cascading framework was built in a hierarchical structure that considers the interrelationships between the integrated energy components leading to seamless modelling of whole operation as a single system. The performance of the proposed H2M-LSTM was compared against a variety of well-known machine learning algorithms through an extensive experimental analysis. The efficacy of the proposed energy framework was demonstrated in comparison to the modelling performance of the individual components, by utilizing three prediction performance indicators. The findings of the present study offer: (i) insights on the low-error performance of tailor-made LSTM architectures fitting the TES modelling problem, (ii) deeper knowledge of the behaviour of integral energy frameworks operating in fine timescales and (iii) an alternative approach that enables the real-time or semi-real time deployment of TES modelling tools facilitating their use in real-world settings.

Estimating the state of charge in a latent thermal energy storage heat exchanger based on inlet/outlet and surface measurements

• Estimators for the total and partial stored energy are developed and validated. • The estimator for the heat transfer fluid energy is generally applicable. • A finite volume latent thermal energy storage model is developed and fitted. The performance of latent thermal energy storage (LTES) heat exchangers is related to the stored energy (i.e. state of charge) during the (dis)charging of the energy storage system. Therefore, measuring the stored energy is crucial to understand the behavior of LTES systems. However, technical considerations often oppose the measurability of the stored energy. The present article presents a case where only measurements at the in- and outlet of the heat transfer fluid and on the outer surface of the heat exchanger were possible. Based on this sparse set of measurements, estimators for the stored energy are developed. To test these estimators, a finite volume model of the LTES heat exchanger is made. The finite volume model is fitted by comparing the predicted heat transfer fluid outlet temperature for 36 experiments. The energy estimators are compared to simulation results. The estimators for the stored energy in the heat transfer fluid, metal and phase change material obtain an average deviation of respectively 0.5 %, 3.9 % and 0.6 % with the stored energy predicted by the finite volume model. The estimator for the stored energy in the heat transfer fluid should be applicable to all LTES heat exchangers while the applicability of the estimators for stored energy in the metal and phase change material depend on small temperature differences between surface and interior of the metal and negligible heat losses.

Investigating energy performance of large-scale seasonal storage in the district heating system of chifeng city: Measurements and model-based analysis of operation strategies

This paper presents a modeling and simulation method that supports energy performance assessment and operation strategy investigation of borehole thermal energy storage in the Chifeng district heating (DH) system. A living laboratory in Chifeng, China that integrates a 0.5 million m3 borehole thermal energy storage system, an on-site solar thermal plant and excess heat from a copper plant is presented. The research adopts Modelica models from open source libraries to evaluate the system. The validity of the borehole thermal energy storage model is evaluated through an inter-model comparison study and an empirical validation test. We used the validated model to investigate three operation strategies. We conclude that the time-scheduled combined operation strategy is more beneficial for the studied system regarding CO2 emission reduction.

Distributed Thermal Energy Storage Configuration of an Urban Electric and Heat Integrated Energy System Considering Medium Temperature Characteristics

Distributed thermal energy storage (DTES) provides specific opportunities to realize the sustainable and economic operation of urban electric heat integrated energy systems (UEHIES). However, the construction of the theory of the model and the configuration method of thermal storage for distributed application are still challenging. This paper analyzes the heat absorption and release process between the DTES internal heat storage medium and the heat network transfer medium, refines the relationship between heat transfer power and temperature characteristics, and establishes a water thermal energy storage and electric heater phase change thermal energy storage model, considering medium temperature characteristics. Combined with the temperature transmission delay characteristics of a heat network, a two-stage optimal configuration model of DTES for UEHIES is proposed. The results show that considering the temperature characteristics in the configuration method can accurately reflect the performance of DTES, enhance wind power utilization, improve the operation efficiency of energy equipment, and reduce the cost of the system.

Optimum Placement of Heating Tubes in a Multi-Tube Latent Heat Thermal Energy Storage

Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes revealed that based on the Taguchi method, the first row of the heat transfer fluid tubes should be located at the lowest possible area while the other tubes should be spread consistently in the enclosure. The charging rate changed by 76% when varying the locations of the tubes in the enclosure to the optimum point. The development of streamlines and free-convection flow circulation was found to impact the system design significantly. The Taguchi method could efficiently assign the optimum design of the system with few simulations. Accordingly, this approach gives the impression of the future design of energy storage systems.

Numerical Modeling of Thermal Energy Storage of CHPs in Porous Concrete

Energy storage is essential in the modern age because fossil energy sources are running out, so there are a variety of ways to store energy, such as operating costs, energy consumption. The primary emissions and emissions, or all three, are reduced. In this paper, the heat energy storage method is used as sensible heat. The primary purpose of this study is to use inexpensive and available materials for energy storage. The heat source in this study is the CHP system exhaust gas selected for a 10-unit residential building. Thermal energy storage material is porous concrete that stores thermal energy in perceptible heat. The modeling of the system was also performed for the storage of thermal energy (charge and discharge process) by Schumann equations for fluid and solid storage in the porous medium, and the numerical solution of the equations was done by the characteristic method. For the fluid charge process of the CHP exhaust gases and air for the fluid discharge process, the porous concrete tank is assumed to be coated with mineral wool thermal insulation without loss of thermal energy. Heat transfer is only considered as one-dimensional heat transfer along the vertical axis of the tank, due to the porous solid storage environment, the conductive heat transfer in all dimensions of the tank is ignored. The thermocline property of the storage tank is essential for the numerical solution of the Schumann equations for the tank, with a charging time of 6 and a half hours and a discharge time of 5 hours.

Multiscale Modeling of Power Plant Performance Enhancement Utilizing Asynchronous Cooling With Thermal Energy Storage

Abstract This study links a model of thermal energy storage (TES) performance to a subsystem model with heat exchangers that cool down the storage at night; this cool storage is used to precool the air flow for a power plant air-cooled condenser during peak day temperatures. The subsystem model is also computationally linked to a model of Rankine cycle power plant performance to predict additional power the plant could generate due to the additional cooling. The model was used to explore the effects of varying phase change material (PCM) melt temperature and the energy input and rejection control settings with the goal of maximizing efficiency for a 50 MW power plant operating in the desert regions of Nevada for an average summer day. The results suggest that the kWh output of the modeled plant can be increased by up to 3.25% during the heat input/cold extraction period, and a cost analysis estimates that the TES system has the potential to provide additional revenue of up to $686,000 per year, depending on electricity cost and parameter choices.

Modeling, transient simulations and parametric studies of parabolic trough collectors with thermal energy storage

For investigating the system response of parabolic trough collector heat generating system, a plant with parabolic trough collector field and two-tank molten salt thermal energy storage model with component-level control algorithm is developed for managing various working conditions. The model is transient inside the components and responds with hourly weather and demand data. The main purpose of this work is providing an alternative design methodology that focuses on the collector field, and storage size by investment, location, and load type.Using a simple economic model, the plant parameters are calculated, which contains only initial investment costs of the parabolic trough collector field and thermal energy storage costs. Depending on the economic model, various sizes of collector field and storage combinations are created at fixed initial investment costs in the mathematical model. A parametric study is performed by using the economic model simulating at several initial investment costs, two different locations in Turkey, and four different load profiles.As a result of the parametric study, maximum solar fraction cases are selected and the generalized trend is observed. The effect of thermal energy storage on the solar fraction is discussed and the change in thermal energy storage with optimum plant size is investigated. After the optimum investment, the linear increment trend of dispatchability is disappearing and increases asymptotically by increasing the plant and/or storage size. Later in this work, the significance of the load profile is emphasized, which should be one of the major design parameters for solar-powered energy systems.

Coupled thermo-fluidic model for thermal energy storage based on liquid solid phase change

The production and storage of thermal energy are important processes that contribute to the satisfaction of daily needs. They are effective ways of managing the thermal energy available from various solar applications. The most efficient storage technique is the use of phase change materials (PCMs) because these components can keep large amounts of thermal energy in stock. The problem is that this approach continues to be confronted with difficulties despite significant progress in research, design and modelling. Nevertheless, these difficulties can be resolved through numerical simulations that enable the identification of powerful tools for optimising thermal system design and predicting thermal behaviour. Correspondingly, in this work, thermo-mechanical modelling was conducted to describe the different methods of heat transfer that can optimise thermal energy storage via PCMs. This study also established a numeric resolution and the spatio-temporal discretisation of the basic equations accompanying the numerical model. The proposed numerical solution improves the prediction of thermal behaviour and can be used as a guide in designing new systems capable of producing and storing solar energy.

A porous medium based heat transfer and fluid flow model for thermal energy storage in packed rock beds

Thermal energy storage in packed rock beds helps to reduce energy costs and carbon footprint’s on an industrial, commercial and residential scale. Fluid flow and heat transfer in large-size packed rock beds used in mining applications such as heating/cooling of mine intake air or ventilation of block-caved mines have recently received significant attention. Understanding the porous structure of such packed rock beds is a necessity in the design of such systems. The pressure drop across a rock bed directly affects its heat exchange performance, as it requires additional fan power to circulate air during periods of storage/extraction. In this study, the fluid flow behavior inside a packed rock bed thermal energy storage system is investigated by developing a computational fluid dynamics model and a heat transfer model. The model offers useful information for evaluating the performance of rock beds packed with large rocks or in caved zones. Finally, the main goal of this study is to perform a practical energy saving analysis for porous media composed of large particles by changing the physical properties of the porous medium, such as porosity and permeability. The findings of this study also show that while the total thermal energy storage capacity of the system is not significantly affected by the mass flow rate, a lower mass flow rate can provide a longer working period for thermal energy storage systems.

A General Model for Thermal Energy Storage in Combined Heat and Power Dispatch Considering Heat Transfer Constraints

Heat transfer (HT) is a major constraint in thermal system analysis. However, when discussing utilizing the flexibility provided by the heating sector, for example, using thermal energy storage (TES) to increase operational flexibility of combined heat and power (CHP), the HT process is often ignored. This may mean infeasibility of the resulting schedules. In response to this, this paper proposes a general TES model which takes detailed HT analysis into account. By setting the relevant parameters, this model can be used to describe the HT process for both sensible heat (SH) and latent heat (LH) TES devices. An iteration method is proposed to deal with the nonlinearity introduced by the HT constraints, and to solve the joint nonlinear dispatch problem for CHP with TES. The simulation results show that explicitly considering the HT process is essential to realistically assess and therefore make full use of the flexibility provided by TES. Moreover, the comparison between LH and SH TES shows that LH can provide more flexibility for the system, especially when the starting energy level in the TES device is low.