0
Research Papers: Energy Systems Analysis

# Energy and Cost Analysis of a New Packed Bed Pumped Thermal Electricity Storage UnitOPEN ACCESS

[+] Author and Article Information
Alberto Benato

Mem. ASME
Department of Industrial Engineering,
Via Venezia, 1,
e-mail: alberto.benato@unipd.it

Anna Stoppato

Professor
Mem. ASME
Department of Industrial Engineering,
Via Venezia, 1,
e-mail: anna.stoppato@unipd.it

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received January 31, 2017; final manuscript received September 20, 2017; published online October 31, 2017. Assoc. Editor: George Tsatsaronis.

J. Energy Resour. Technol 140(2), 020904 (Oct 31, 2017) (7 pages) Paper No: JERT-17-1052; doi: 10.1115/1.4038197 History: Received January 31, 2017; Revised September 20, 2017

## Abstract

Renewable energy sources (RES) are quite capable to actively contribute to meet the today's energy demand. However, many of them have a time-dependent nature that constitutes their major disadvantage. To overcome this drawback, energy storage systems (ESS) need to be set up. In this way, the stored energy can be used in the absence of RES or under peak demand hours. High-temperature pumped thermal electricity storage (PTES) using packed bed constitutes an attractive solution but is characterized by high losses and irreversibilities. For this reason, in this paper, a new plant scheme is presented and its mathematical model built up. To predict the packed bed behavior, a one-dimensional two phase model of the hot and cold storages has been included, while the plant feasibility is evaluated using an energy and a cost analysis. Results show that the highest quantity of energy and round-trip efficiency are reached with a packed bed made of magnetite and titanium oxide.

<>

## Introduction

Nowadays, the total primary energy consumption of the world is based on nonrenewable energy sources (coal, natural gas, and oil) which account for more than 85% [1]. Nevertheless, the use of these sources creates environmental and economic issues. Therefore, the exploitation and utilization of renewable energy sources (RES) has become essential.

Renewable resources, such as wind and solar, are environmental friendly but highly variable, uncontrollable, and unpredictable. These aspects combined with the deregulation of the electricity market, the rapid growth of renewable energies, the need of network flexibility, and improved grid side management are gaining the interest on energy storage systems (ESS).

As an example and with the purpose of understanding the scale of the problem, Koytsoumpa et al. [2] investigated the European Union electricity markets and underlined the need of installing large-scale energy storage and flexible conventional plants and improving RES-technology, the Pan-European grid, and the transmission technologies. Therefore, there is a urgent need of developing new and smaller-footprint large-scale storage units.

For this reason, in this work, an energy and cost analysis of a new pumped thermal electricity storage (PTES) configuration is presented. As in conventional PTES units, the plant consists of a high pressure and temperature tank, a low pressure and temperature tank, two turbomachines (a compressor and a turbine), and an electric motor/generator. The novelty of the proposal consists on an electric heater, which converts the electrical energy into thermal energy instead of the compressor, and on the use of one heat exchanger instead of two. In order to compute the system efficiency during charging and delivering time, a detailed mathematical model of the reservoirs has been built in matlab environment. Then, the plant round-trip efficiency and its economic feasibility have been estimated.

The rest of the work is organized as follows: In Sec. 2, a brief overview of the large-scale energy storage technologies is presented, while the new PTES scheme and its mathematical model are presented in Sec. 3. In Sec. 4, the results of the simulations are presented and discussed, while in Sec. 5 some concluding remarks are given.

## Large-Scale Energy Storage Technologies

At the time of writing, there are several more or less mature storage technologies [36]: flywheels, super capacitors, batteries and flow batteries (FBs), compressed air energy storage (CAES), superconducting magnetic energy storage, pumped hydrostorage (PHS), PTES, and hydrogen energy storage, each one having its own scale of application, advantages, and drawbacks.

Despite the large number of available ESS, only PHS, CAES, FB, PTES, and hydrogen storage are able to store up to 100 MWh, and then can be considered large-scale energy storage technologies.

The PHS plant is composed by an upper reservoir, a waterfall, and a lower reservoir. Energy is stored in the form of gravitational potential energy of water; the stored energy (up to several gigawatt-hours) depends to the water volume contained in the upper reservoir and the height of the waterfall [7]. During off-peak hours, the low cost electricity is used to pump the water from the lower elevation reservoir to the upper one, while, during high electrical demand hours, the stored water is released back into the lower reservoir through turbines to produce again electric power. A PHS plant can respond to load changes within seconds; then, this technology is essential to control the electric network frequency and provide reserve generation. Being PHS the most cost effective way of storing large amounts of electrical energy, this technology is become the dominant large-scale energy storage technology with over 96% of the world's installed storage capacity. However, geographical constraints and high initial cost mean a rapid development only in countries with favorable morphology like the U.S.

Compressed air energy storage is an in-developing technology, but it is the leading competitor to PHS due to its capacity of storing several hundreds of megawatt-hour. Around the world, only two plants exist, one in Germany and one in the U.S. [8]. CAES plants are based on gas turbine technology, and the energy is stored in form of compressed air in an underground cavern. The gas turbine is split into two parts that are operated separately. During low demand hours, the low cost electricity is used to pump air into the underground cavern at a pressure higher than 70 bar. To limit the compressor outlet temperatures, multiple stage intercooling are used. During peak demand hours, the compressed air stored in the cavern is mixed with natural gas and burnt into the gas turbine combustion chamber. Then, the exhaust gases are, first, expanded into a high-pressure turbine, reheated, and afterward expanded into the low-pressure turbine. The turbines are connected to an electric generator in order to produce electrical energy, while the turbines' exhaust gases are used to heat the air coming from the cavern before it enters into the combustion chamber. CAES plants are characterized by a very low self-discarded time, a life higher than 30 yr, and an energy efficiency greater than 70%. To date, several configurations are under analysis (see, e.g., Refs. [810]) but it is expected that has a rapid commercial development only in countries with favorable geology, such as the U.S.

Flow batteries are a recent technology, which employs two different aqueous electrolytic solutions contained in separate tanks. The operating principle is based on reversible electrochemical reactions that occur in a set of cells [11]. FBs are able to store hundreds of megawatt-hour but, compared to PHS and CAES, are characterized by a limited output power.

Pumped hydrostorage, CAES, and flow batteries are commercially available large-scale electricity storage technologies, while hydrogen storage and PTES are emerging large-scale ESS.

Hydrogen can be stored as a compressed gas, a cryogenic liquid, or by a binding process which tie up hydrogen with another compound. Actually, compressed hydrogen and liquid hydrogen are the most used methods to store hydrogen. Despite the large number of available works (see, e.g., Refs. [9] and [1214]), several efforts need to be done in order to develop a safe, efficient, and economically feasible hydrogen storage system.

Pumped thermal electricity storage or “pumped heat electricity storage” is the other really promising large-scale energy storage technology. The working principle is really simple: the plant works as an high-temperature heat pump cycle during changing phase, while during delivering period it works as a thermal engine cycle. The high-temperature heat pump cycle transforms electricity into heat and stocks it into two thermal reservoirs, while the thermal engine cycle converts the stocked energy into electricity. The PTES plant is composed by a compressor (COMP), an expander (EXP), and two thermal reservoirs: one hot (HS) and one cold (CS). Typical temperature and pressure in the hot storage are, respectively, 500–1000 °C and 4–10 bar, while in the cold reservoir temperature and pressure are −150 to −70 °C and 1 bar, respectively. The reservoirs are arranged vertically, the energy is stored as sensible heat, and the working fluid is a gas: argon. The heat exchangers (HX1 and HX2) are used to maintain the compressor and turbine inlet temperature at constant values [1517]. For clarity, the plant layout proposed by White et al. [15] is depicted in Fig. 1.

Regarding PTES technology, several independent patents have been filled, while, in literature, only few theoretical works are available [1519]. For clarity, a brief discussion of these works is reported later.

Desrues et al. [16] built the PTES numerical model with the aim of demonstrating the process feasibility. The storage reservoirs are characterized by a volume of 21,622 m3, while the estimated storage capacity and efficiency are 602.6 MWh and 66.7%, respectively. Desrues et al. found that the charging and discharging time are, respectively, 6 h 3 min and 5 h 52 min, while they concluded that the model needs to be validated with test rig which includes two large storage tanks.

Howes [18], Thess [19], White et al. [15], and McTigue et al. [17] also performed theoretical investigations on PTES systems. The first one developed a numerical model of a 2 MW PTES system with 16 MWh of storage, while Thess analyzed a generic “endoreversible” PTES system.

White et al. [15] investigated the PTES energy and power density, the sources of irreversibility, and their impact on round-trip efficiency. Results showed that a higher round-trip efficiency can be achieved using reciprocating devices instead of turbomachinery, while the effects of compression and expansion irreversibility can be mitigated by reducing the ratio between hot and cold store discharged temperatures.

Similarly to Ref. [15], McTigue et al. [17] analyzed the PTES thermodynamic aspects but they concluded that the round-trip efficiency is sensitive to the loss factors that occur in compressions and expansions processes during charge and discharge cycle.

Finally, Frate et al. [20] proposed a theoretical study of an integrated PTES able to boost the electric round-trip efficiency.

In the previously mentioned works, the researchers proposed different kinds of storage materials which can be used to store the energy as sensible heat. Therefore, in order to identify the most appropriate storage medium, an extensive literature review has also been conducted.

Pumped thermal electricity storage employs sensible heat storage and a gas as working fluid. Therefore, as remarked in Ref. [21], packed bed is the most convenient storage system. A packed bed storage system consists of loosely packed solid material through which the heat transport fluid is circulated. The shape and size of the storage are a function of several parameters (storage medium and temperature, storage heat losses, insulation material, type and size of the heat exchangers, and operating conditions), while the storage material needs to be inexpensive, nontoxic, nonflammable, with high thermal diffusivity, good conductive characteristics and does not require a large heat transfer area. All these characteristics can be found in materials like rocks, metals, concrete, sand, and brick. In addition, these materials can be used for both low and high-temperature sensible heat storage. Obviously, appropriate tanks insulation needs to be set up as well as a relative small distance between the plant devices [21].

Based on the literature review, it is possible to conclude that packed bed is the most suitable manner to store sensible heat because it is characterized by low pressure drop, while PTES plants suffer of high irreversibilities and losses in compressor and expansion processes and in the heat exchangers used to maintain the compressor and the turbine inlet temperatures at the prefixed value. With the aim of improving the plant efficiency and reducing the system cost, the authors have developed a new PTES architecture.

## The New Pumped Thermal Electricity Storage Scheme and Its Mathematical Model

The architecture of the new PTES plant used during charging phase is depicted in Fig. 2, while Fig. 3 shows the plant arrangement used during delivery period.

The system consists in a high pressure and temperature tank (HS) and a low pressure and temperature tank (CS), two turbomachines (a COMP and a turbine (EXP)), an electric motor/generator (MG), an electric heater (HEATER or EH), and a heat exchanger (HX).

During the charge (Fig. 2), the machines force the air to follow the way 1 – > 6 which is not exactly a heat pump cycle that absorbs heat from the cold tank and brings it to the hot one because after the compressor there is an electric heater. The electric heater is one of the novelty of the proposal, and it is used to increase the fluid temperature.

In previous PTES plants [1517], the electrical energy is converted into thermal energy by means of the compression process; therefore, high temperature means high pressure ratio which in turn implies high cost for the hot reservoir. In the proposed scheme, the temperature at the HS tank inlet section is independent from the compression pressure ratio. In addition, the insertion of an electric heater allows to work with a not fixed compressor inlet temperature; mandatory condition in the scheme presented in Refs. [1517]. The electric heater allows to maintain T3 equal to the maximum cycle temperature (Tmax) and to reduce the compressor pressure ratio and, subsequently, the costs of the compressor. The hot tank storage material, initially at ambient temperature (Tamb), is slowly heated by the hot air entering at Tmax but also the air's temperature that leaves the HS raises up. A heat exchanger is, therefore, necessary between the hot tank and the expander to keep the turbine inlet temperature at its design value (T5 = Tamb). After the expansion, the air is injected into the cold reservoir. The cold tank storage material, initially at Tamb, is slowly cooled by the cold air (at a temperature equal to the minimum cycle temperature Tmin) coming from the outlet section of the turbine. The motor–generator machine is mechanically coupled with the compressor and the turbine. Note that, during the charging phase, it acts as an electric motor, while during delivery period it works as a generator. Finally, the cycle is closed because the compressor sucks the air exiting the cold storage. Note that, in previous works [1517], a second heat exchanger is inserted between the cold storage and the compressor to maintain the COMP inlet temperature at its design value. In the proposal, only the heat exchanger between the hot tank and the expander is required; a novelty that reduces the plant purchasing costs and the irreversibility.

During the delivering phase (Fig. 3), air follows along the route 11–14 which corresponds to a heat engine cycle. The air that leaves the compressor, enters into the hot storage, is heated up, and leaves the HS at a temperature approximately equal to Tmax. Then, the working medium is expanded in the turbine and injected into the cold reservoir. Here, it is cooled and, when it leaves the tank, its temperature is approximately equal to Tmin. Similarly to the charging period, the packed bed of the cold storage is slowly heated up by the warm gas that lives the expender, while the hot storage packed bed is slowly cooled down by the gas that lives the compressor.

As in the other PTES plants, the working fluid is a gas. For simplicity and with the aim of reducing the plant operating cost, air is used as working medium instead of argon. Air is an abundant, freely available, nontoxic, and inflammable working fluid that can be easily used all around the world.

The compressor and the expander can be either turbomachinery-based or reciprocating devices. In the proposed layout, there is the need of two machines because the same compressor and turbine are used during charging and delivering phase. Note that in Ref. [16], four machines are needed: one compressor/turbine pair is used during the charging phase, while the another one is used during the delivery period. In this work, the authors assumed that compressor and turbine are turbomachinery. Both of them are mechanically coupled and linked to the motor–generator.

The hot and cold tanks are arranged vertically to prevent buoyancy-driven instabilities of the hot and cold thermal fronts. The reservoirs are cylinder with an upper plenum, a packed bed, and a lower plenum. During charging phase, the air flows in the hot tank from the top to the bottom section, while, during delivery period, the air flow is reversed. As depicted in Figs. 2 and 3, the air flows through the cold storage from bottom to top during the charge, while, during delivery period, the air flow is reversed.

The hot and cold packed beds are made of randomly packed aluminum oxide spheres. Being the spheres randomly packed, the void fraction is 0.4, while it is assumed that the spheres diameter and sphericity are equal to 0.05 m and 1, respectively. It is also assumed that the hot and cold packed bed initial temperature is equal to 25 °C which is the ambient temperature. As suggested by Poling et al. [22], the aluminum oxide density is assumed constant and equal to 3990 kg/m3 in both the working temperature ranges (in the cold reservoir is TminTamb, while in the hot one is TambTmax), while the material specific heat changes with the temperature. For this reason, the specific heat is an average value computed at an average temperature between the bed initial temperature (Tamb) and the maximum (Tmax) or minimum (Tmin) one as suggested in Ref. [23]. The aluminum oxide specific heat versus temperature curve derived from Ref. [24] has been uploaded into the PTES mathematical model, and, after the definition of Tmax, Tmin, and Tb,i, the average hot and cold bed temperatures are computed. In the case under analysis, the CS and HS average temperatures are −22.5 °C and 282.5 °C, respectively. Then, fitting the specific heat versus temperature curve, the specific heat is 67 J/(mol K) in the case of the cold storage and 110 J/(mol K) for the hot storage.

To predict the thermal performance of the packed bed, the Mumma and Marvin model has been adopted [25]. It is a one-dimensional transient analysis of energy exchange between the gaseous stream and the bed material elements, using a finite difference method. In the model, it is assumed that the fluid is Newtonian, the solid and the fluid have constant properties, there is no internal heat generation, no mass transfer, a negligible heat conduction in the fluid phase, and negligible radiation heat transfer between the bed and the fluid compared to forced convection. With the aim of precisely predict both temperature trends and pressure drops, each tank has been discretized in “N” elements of equal axial thickness (Δx), as shown in Fig. 4.

As said, the Mumma and Marvin governing equations are used to predict both the air and the solid temperature distribution, while the pressure drop and the volumetric heat transfer coefficient are, respectively, computed using the friction factor and the Nusselt number equations proposed by Singh et al. [26]. The storage dissipations to the environment have been neglected because it has been assumed to insulate the reservoirs with an appropriate material and to adopt a management strategy which charge and discharge the reservoirs at least one time per day.

Finally, it is assumed that the packed bed volume and the storage height are 150 m3 and 10 m, respectively, while each reservoir is discretized in 70 layers. The air mass flow rate and the pressure ratio have been assumed equal to 15 kg/s and 6, respectively, while the compressor and turbine isentropic efficiency are both equal to 0.8. The working medium (air in this study) thermodynamic properties have been retrieved from Ref. [27] and uploaded at each iteration and in each point of the plant.

Being the authors' aim of installing the proposed PTES plant instead of an underutilized thermal power plant and arranging the energy storage unit with already available devices of the thermal power plant, the assumed parameters have been selected in such a way that the PTES is used to revamp an existing Italian power unit characterized by low operational utilization factors in integrated energy storage systems without installing additional capacity.

## Results

Firstly, the packed bed has been validated using the storage and bed elements geometry and the material properties listed in Ref. [26]. The obtained temperature and pressure trends differ less 1% with the ones reported in the reference. Then, the Desrues et al. plant arrangement described in Ref. [16] has been built and simulated in matlab environment. Results highlighted that the highest losses are in the heat exchangers, while the compressor and the expander are the source of irreversibilities. Finally, the model of the proposal has also been built in matlab environment and linked with the fluid and the material database [24,27].

At the initial conditions, the tanks are at the ambient temperature; then, air slowly heated up the hot storage, while it cooled down the cold reservoir. At the end of the charge (in the analyzed case after 9.3 h), the storages are at 540 °C and −70 °C, respectively. In the matlab model, a control system has been implemented in order to stop the charge when the temperature difference between the tank outlet temperature and its prescribe design temperature exceeds a given relative threshold called TtolDisplay Formula

(1)$T4≥Tmax−Ttol and T1≤Tmin+Ttol$

where Ttol (assumed in this work equal to 7 °C) is the maximum admissible temperature reduction. For the charging phase, the adopted management strategy allows to obtain mean temperatures of the hot and cold packed bed nearly equal to the one of the air which enters into each tank (540 °C and −70 °C in HS and CS, respectively).

In order to present the model capability of predicting the temperature trends of each layer, Fig. 5 depicts the temperature trend of each bed layer during the charge process.

The delivery phase starts with a hot and cold packed bed temperature approximately equal to 540 °C and −70 °C, respectively. During the discharge, the hot reservoir is slowly cooled, while the cold one is slowly heated up. The delivery phase ends when the produced power is 5% lower than the initial value. The temperature trend of each layer of the tanks during delivery is depicted in Fig. 6.

As said, the first charge requires 9.3 h, while the discharge has a duration of 2.8 h. The system reaches the stability after the first charge–discharge cycle. Then, from the second to the “jth” charge, the requested charge time is 5.6 h, while the discharge time remains 2.8 h because the initial discharge conditions remain always the same with the adopted management strategy.

During the discharge, the output power is 1.64 MW and is approximately constant. Then, the plant can provide 4.7 MWh. This is due to the implemented control system which stops the discharge phase when the produced power is 5% lower than the start value. Obviously, to better evaluate the proposed plant performance, in future works, it can be useful to simulate a real day charge–discharge cycle.

Figure 7 shows the temperature trends of the first and the last layers of the hot and cold storages during two charge/discharge cycles. It is immediately clear that the hot reservoir is fed from the top during the charging phase, while the flow is reverse during the delivery period. This means that, during the charge, the hot tank first layer is the first that reaches the maximum cycle temperature (540 °C), while, during the delivery, it is also the layer that undergoes the smallest temperature drop. On the contrary, the HS last layer is the one subjected to the highest temperature difference because it is the last layer to be heated up during the charge but the first to be cooled during the delivery. As clearly shows in Fig. 7, the cold tank first and last layers are subjected to a similar trend.

It is also interesting to plot the trends of the power in the plant components during the first charge and discharge (see Fig. 8). At the beginning of the charging phase, the power dissipated by the heat exchanger (PHX) is equal to 0 MW until the hot storage packed bed temperature remains approximately equal to the ambient temperature. But, when the temperature of the last layer of the hot storage is starting to rise up, also the HX dissipated power is starting to rise up because there is the need of maintaining the expander inlet temperature constant and equal to its design value. In this way, power produced by the expander (PEXP) remains constant, while the one absorbed by the compressor (PCOMP) decreases because the air temperature at the compressor inlet section decreases too. The air temperature is increased using the electric heater which absorbs PEH from the grid: a simple and controllable manner to heat a gaseous fluid. Compared to other PTES configurations, there is no need of adopting high pressure ratios to reach high temperature in the hot storage because it is the electric heater that heat up the air absorbing PEH from the grid and not the compressor. In addition, only an heat exchanger is required during the charge to maintain constant the expander inlet temperature: an effective manner to reduce purchase cost and system irreversibilities. Despite these positive aspects, the heat released by the HX during the charge constitutes an energy loss because it cannot be considered a useful product.

During the delivery, no heat exchangers are required. Then, the reservoirs temperature varies and the delivery process stops when, again, the produced power becomes 5% lower than the design one.

The plant cost has been estimated with the equations presented in Refs. [2830] and based on the knowledge of an industrial partner which has also provide the packed bed material cost (e.g., Al2O3 specific cost is 1500 US$/ton). Following the specifications reported in Ref. [31], the round-trip efficiency is computed as Display Formula (2)$η=∫tstart dischargingtstop discharging(P EXP −PCOMP)dtdischarging∫tstart chargingtstop charging(PEH−P EXP +PCOMP)dtcharging$ In the case under analysis, the round-trip efficiency, the total purchase cost, and the pressure drops are 15.35%, 5.10 M$, and 1 bar in each reservoir.

The poor round-trip efficiency is due to the energy rejected to the environment with the heat exchanger during the charge, the limited value of the maximum cycle temperature, and the adopted control strategy. In fact, with a management strategy which stops the discharge when the produced power is 30% lower than the starting value, the round-trip efficiency becomes 22%. The computed pressure drops seem acceptable because, also in Ref. [16], the authors underlined that pressure drops in the tanks are really few but, in the authors' point of view, additional investigations need to be done. For this reason, a thermofluid-dynamic analysis is expected to be done with the aim of evaluating the velocity flow field and the pressure drop in the tanks.

Being the round-trip efficiency and the plant cost strictly dependent to the storage medium, aluminum oxide (Al2O3), titanium oxide (TiO2), iron oxide—hematite (Fe2O3), and iron oxide—magnetite (Fe3O4) have been tested to find out the material which guarantees the highest round-trip efficiency. These materials have been selected based on the work presented in Ref. [23]. As for Al2O3, the material properties of TiO2, Fe2O3, and Fe3O4 are derived from Refs. [22] and [24], and the related cost is based on the knowledge of an industrial partner.

Table 1 listed the assumed bed materials characteristics, while Table 2 summarized the main results. These results have been obtained using the same storage volume, maximum and minimum temperature, and bed material shape, diameter, void fraction, and sphericity.

The highest quantity of energy and round-trip efficiency are reached with a bed made of magnetite and titanium oxide, respectively. The fastest charge–discharge cycle is reached with a bed made of TiO2 but, due to the high cost per ton of the bed material, this plant is the most expensive one. Fe2O3 and Fe3O4 are the cheapest materials to make the packed bed but also the ones that guarantee to build the cheapest system.

Despite the poor round-trip efficiency, the proposed PTES scheme is considered an emerging large-scale storage method for electric applications. Therefore, a comparison among PHS, CAES, batteries (NaS and ZEBRA), and PTES in term of energy density and price per unit of energy stored is given considering that 1 Euro = 1 US$and based on the estimations listed in Refs. [15] and [32]. Considering a storage volume of 300 m3, the plant cost, and the energy stored listed in Table 2, the energy density ranges between 178 and 220 kWh/m3, while the price per unit of energy stored is in the range 48–103 Euro/kWh. Considering that the energy density and the price per energy unit stored are 0.5–1.5 kWh/m3 and 10–70 Euro/kWh for PHS and 3–6 kWh/m3 and 2–140 Euro/kWh for CAES, the proposed plant configuration is able to compete with these technology, but without the geographic constrains because the reservoirs are man-made devices. ## Conclusions Pumped thermal electricity storage is an attractive energy storage technology, but previous investigations have underlined the necessity of reducing losses and irreversibilities. For this reason, in this work, a new plant scheme has been presented, modeled, and tested. In the proposal, the maximum temperature is maintained at a constant value using an electric heater. Therefore, the maximum cycle temperature can be easily increased/decreased in accordance with the amount of energy that needs to be stored. The second novelty of the proposal is the need of a unique heat exchanger during the charging phase and no heat exchangers during the delivery period. This plant arrangement allows to reduce the plant irreversibilities and losses. Being the packed bed storage material a key parameter, four types of storage material have been tested. The highest quantity of energy and round-trip efficiency are reached with a bed made of magnetite and titanium oxide, respectively, while Fe2O3 and Fe3O4 are the cheapest materials to make the packed bed. Comparing PHS and CAES with the new PTES layout, it is possible to observe that the proposal has higher energy density and comparable price per energy unit stored. Therefore, this new PTES scheme is a valid alternative to CAES and PHS. In addition, being the reservoirs man-made tanks, it does not suffer of geographical constrains and can be built with already available components taking from, e.g., underutilized thermal power units and does not present geographical limitations because the reservoirs are man-made devices and have higher cycle life than flow batteries. ## Nomenclature • a = air • amb = ambient • b = bed • C = cost,$

• Cp =

specific heat, J/(mol K)

• ch =

charge

• dis =

discharge

• E =

stored energy, MWh

• max, min =

maximum, minimum

• P =

power, MW

• t =

time, h

• T =

temperature, K or °C

• tol =

tolerance

• Δ =

difference

• η =

efficiency, %

• ρ =

density, kg/m3

## References

Dincer, I. , 1998, “ Energy and Environmental Impacts: Present and Future Perspectives,” Energy Sources, 20(4–5), pp. 427–453.
Koytsoumpa, E.-I. , Bergins, C. , Buddenberg, T. , Wu, S. , Sigurbjörnsson, Ó. , Tran, K. , and Kakaras, E. , 2016, “ The Challenge of Energy Storage in Europe: Focus on Power to Fuel,” ASME J. Energy Resour. Technol., 138(4), p. 042002.
Ibrahim, H. , Ilinca, A. , and Perron, J. , 2008, “ Energy Storage Systems—Characteristics and Comparisons,” Renewable Sustainable Energy Rev., 12(5), pp. 1221–1250.
Coppez, G. , Chowdhury, S. , and Chowdhury, S. , 2010, “ The Importance of Energy Storage in Renewable Power Generation: A Review,” 45th International IEEE Universities Power Engineering Conference (UPEC), Wales, UK, Aug. 31–Sept. 3, pp. 1–5.
de Sisternes, F. J. , Jenkins, J. D. , and Botterud, A. , 2016, “ The Value of Energy Storage in Decarbonizing the Electricity Sector,” Appl. Energy, 175, pp. 368–379.
Stoppato, A. , and Benato, A. , 2017, “ The Importance of Energy Storage,” Energy Storage, World Scientific, Singapore.
González, A. , McKeogh, E. , and Gallachoir, B. , 2004, “ The Role of Hydrogen in High Wind Energy Penetration Electricity Systems: The Irish Case,” Renewable Energy, 29(4), pp. 471–489.
Herrmann, S. , Kahlert, S. , Wuerth, M. , and Spliethoff, H. , 2017, “ Thermo-Economic Evaluation of Novel Flexible CAES/CCPP Concept,” ASME J. Energy Resour. Technol., 139(1), p. 011902.
Roy, B. U. , and Rengarajan, N. , 2017, “ Feasibility Study of an Energy Storage System for Distributed Generation System in Islanding Mode,” ASME J. Energy Resour. Technol., 139(1), p. 011901.
Mazloum, Y. , Sayah, H. , and Nemer, M. , 2016, “ Static and Dynamic Modeling Comparison of an Adiabatic Compressed Air Energy Storage System,” ASME J. Energy Resour. Technol., 138(6), p. 062001.
Mofidi, S. A. H. , and Udell, K. S. , 2017, “ Study of Heat and Mass Transfer in MgCl2/NH3 Thermochemical Batteries,” ASME J. Energy Resour. Technol., 139(3), p. 032005.
Braun, R. J. , Hanzon, L. G. , and Dean, J. H. , 2011, “ System Analysis of Thermochemical-Based Biorefineries for Coproduction of Hydrogen and Electricity,” ASME J. Energy Resour. Technol., 133(1), p. 012601.
Platzer, M. F. , Sarigul-Klijn, N. , Young, J. , Ashraf, M. , and Lai, J. , 2014, “ Renewable Hydrogen Production Using Sailing Ships,” ASME J. Energy Resour. Technol., 136(2), p. 021203.
McClaine, A. W. , Brown, K. , and Bowen, D. D. , 2015, “ Magnesium Hydride Slurry: A Better Answer to Hydrogen Storage,” ASME J. Energy Resour. Technol., 137(6), p. 061201.
White, A. , Parks, G. , and Markides, C. N. , 2013, “ Thermodynamic Analysis of Pumped Thermal Electricity Storage,” Appl. Therm. Eng., 53(2), pp. 291–298.
Desrues, T. , Ruer, J. , Marty, P. , and Fourmigué, J. , 2010, “ A Thermal Energy Storage Process for Large Scale Electric Applications,” Appl. Therm. Eng., 30(5), pp. 425–432.
McTigue, J. D. , White, A. J. , and Markides, C. N. , 2015, “ Parametric Studies and Optimisation of Pumped Thermal Electricity Storage,” Appl. Energy, 137, pp. 800–811.
Howes, J. , 2012, “ Concept and Development of a Pumped Heat Electricity Storage Device,” Proc. IEEE, 100(2), pp. 493–503.
Thess, A. , 2013, “ Thermodynamic Efficiency of Pumped Heat Electricity Storage,” Phys. Rev. Lett., 111(11), p. 110602. [PubMed]
Frate, G. F. , Antonelli, M. , and Desideri, U. , 2017, “ A Novel Pumped Thermal Electricity Storage (PTES) System With Thermal Integration,” Appl. Therm. Eng., 121, pp. 1051–1058.
Singh, H. , Saini, R. , and Saini, J. , 2010, “ A Review on Packed Bed Solar Energy Storage Systems,” Renewable Sustainable Energy Rev., 14(3), pp. 1059–1069.
Poling, B. E. , Thomson, G. H. , Friend, D. G. , Rowley, R. L. , and Wilding, W. V. , 2008, Perry's Chemical Engineers' Handbook, McGraw-Hill, New York.
White, A. , McTigue, J. , and Markides, C. , 2014, “ Wave Propagation and Thermodynamic Losses in Packed-Bed Thermal Reservoirs for Energy Storage,” Appl. Energy, 130, pp. 648–657.
Lemmon, E. W., McLinden, M. O., and Huber, M. L., 2002, “NIST Standard Reference Database 23-NIST Thermodynamic and Transport Properties REFPROP, Version 7.0,” National Institute of Standards and Technology, Gaithersburg, MD, accessed Oct. 20, 2017,
Howell, J. R. , Bannerot, R. B. , and Vliet, G. C. , 1982, Solar-Thermal Energy Systems: Analysis and Design, McGraw-Hill Education, New York.
Singh, R. , Saini, R. , and Saini, J. , 2006, “ Nusselt Number and Friction Factor Correlations for Packed Bed Solar Energy Storage System Having Large Sized Elements of Different Shapes,” Sol. Energy, 80(7), pp. 760–771.
Bell, I. H. , Quoilin, S. , Wronski, J. , and Lemort, V. , 2013, “ CoolProp: An Open-Source Reference-Quality Thermophysical Property Library,” ASME ORC Second International Seminar on ORC Power Systems, Rotterdam, The Netherlands, Oct. 7–8, pp. 2498–2508.
Sinnott, R. K. , 2009, Chemical Engineering Design: SI Edition, Elsevier, Oxford, UK.
Benato, A. , Kaern, M. , Pierobon, L. , Stoppato, A. , and Haglind, F. , 2015, “ Analysis of Hot Spots in Boilers of Organic Rankine Cycles Units During Transient Operation,” Appl. Energy, 151, pp. 119–131.
Pezzuolo, A. , Benato, A. , Stoppato, A. , and Mirandola, A. , 2016, “ The ORC-PD: A Versatile Tool for Fluid Selection and Organic Rankine Cycle Unit Design,” Energy, 102, pp. 605–620.
Benato, A. , 2017, “ Performance and Cost Evaluation of an Innovative Pumped Thermal Electricity Storage Power System,” Energy, 138, pp. 419–436.
Zhang, H. , Baeyens, J. , Cáceres, G. , Degrève, J. , and Lv, Y. , 2016, “ Thermal Energy Storage: Recent Developments and Practical Aspects,” Prog. Energy Combust. Sci., 53, pp. 1–40.
View article in PDF format.

## References

Dincer, I. , 1998, “ Energy and Environmental Impacts: Present and Future Perspectives,” Energy Sources, 20(4–5), pp. 427–453.
Koytsoumpa, E.-I. , Bergins, C. , Buddenberg, T. , Wu, S. , Sigurbjörnsson, Ó. , Tran, K. , and Kakaras, E. , 2016, “ The Challenge of Energy Storage in Europe: Focus on Power to Fuel,” ASME J. Energy Resour. Technol., 138(4), p. 042002.
Ibrahim, H. , Ilinca, A. , and Perron, J. , 2008, “ Energy Storage Systems—Characteristics and Comparisons,” Renewable Sustainable Energy Rev., 12(5), pp. 1221–1250.
Coppez, G. , Chowdhury, S. , and Chowdhury, S. , 2010, “ The Importance of Energy Storage in Renewable Power Generation: A Review,” 45th International IEEE Universities Power Engineering Conference (UPEC), Wales, UK, Aug. 31–Sept. 3, pp. 1–5.
de Sisternes, F. J. , Jenkins, J. D. , and Botterud, A. , 2016, “ The Value of Energy Storage in Decarbonizing the Electricity Sector,” Appl. Energy, 175, pp. 368–379.
Stoppato, A. , and Benato, A. , 2017, “ The Importance of Energy Storage,” Energy Storage, World Scientific, Singapore.
González, A. , McKeogh, E. , and Gallachoir, B. , 2004, “ The Role of Hydrogen in High Wind Energy Penetration Electricity Systems: The Irish Case,” Renewable Energy, 29(4), pp. 471–489.
Herrmann, S. , Kahlert, S. , Wuerth, M. , and Spliethoff, H. , 2017, “ Thermo-Economic Evaluation of Novel Flexible CAES/CCPP Concept,” ASME J. Energy Resour. Technol., 139(1), p. 011902.
Roy, B. U. , and Rengarajan, N. , 2017, “ Feasibility Study of an Energy Storage System for Distributed Generation System in Islanding Mode,” ASME J. Energy Resour. Technol., 139(1), p. 011901.
Mazloum, Y. , Sayah, H. , and Nemer, M. , 2016, “ Static and Dynamic Modeling Comparison of an Adiabatic Compressed Air Energy Storage System,” ASME J. Energy Resour. Technol., 138(6), p. 062001.
Mofidi, S. A. H. , and Udell, K. S. , 2017, “ Study of Heat and Mass Transfer in MgCl2/NH3 Thermochemical Batteries,” ASME J. Energy Resour. Technol., 139(3), p. 032005.
Braun, R. J. , Hanzon, L. G. , and Dean, J. H. , 2011, “ System Analysis of Thermochemical-Based Biorefineries for Coproduction of Hydrogen and Electricity,” ASME J. Energy Resour. Technol., 133(1), p. 012601.
Platzer, M. F. , Sarigul-Klijn, N. , Young, J. , Ashraf, M. , and Lai, J. , 2014, “ Renewable Hydrogen Production Using Sailing Ships,” ASME J. Energy Resour. Technol., 136(2), p. 021203.
McClaine, A. W. , Brown, K. , and Bowen, D. D. , 2015, “ Magnesium Hydride Slurry: A Better Answer to Hydrogen Storage,” ASME J. Energy Resour. Technol., 137(6), p. 061201.
White, A. , Parks, G. , and Markides, C. N. , 2013, “ Thermodynamic Analysis of Pumped Thermal Electricity Storage,” Appl. Therm. Eng., 53(2), pp. 291–298.
Desrues, T. , Ruer, J. , Marty, P. , and Fourmigué, J. , 2010, “ A Thermal Energy Storage Process for Large Scale Electric Applications,” Appl. Therm. Eng., 30(5), pp. 425–432.
McTigue, J. D. , White, A. J. , and Markides, C. N. , 2015, “ Parametric Studies and Optimisation of Pumped Thermal Electricity Storage,” Appl. Energy, 137, pp. 800–811.
Howes, J. , 2012, “ Concept and Development of a Pumped Heat Electricity Storage Device,” Proc. IEEE, 100(2), pp. 493–503.
Thess, A. , 2013, “ Thermodynamic Efficiency of Pumped Heat Electricity Storage,” Phys. Rev. Lett., 111(11), p. 110602. [PubMed]
Frate, G. F. , Antonelli, M. , and Desideri, U. , 2017, “ A Novel Pumped Thermal Electricity Storage (PTES) System With Thermal Integration,” Appl. Therm. Eng., 121, pp. 1051–1058.
Singh, H. , Saini, R. , and Saini, J. , 2010, “ A Review on Packed Bed Solar Energy Storage Systems,” Renewable Sustainable Energy Rev., 14(3), pp. 1059–1069.
Poling, B. E. , Thomson, G. H. , Friend, D. G. , Rowley, R. L. , and Wilding, W. V. , 2008, Perry's Chemical Engineers' Handbook, McGraw-Hill, New York.
White, A. , McTigue, J. , and Markides, C. , 2014, “ Wave Propagation and Thermodynamic Losses in Packed-Bed Thermal Reservoirs for Energy Storage,” Appl. Energy, 130, pp. 648–657.
Lemmon, E. W., McLinden, M. O., and Huber, M. L., 2002, “NIST Standard Reference Database 23-NIST Thermodynamic and Transport Properties REFPROP, Version 7.0,” National Institute of Standards and Technology, Gaithersburg, MD, accessed Oct. 20, 2017,
Howell, J. R. , Bannerot, R. B. , and Vliet, G. C. , 1982, Solar-Thermal Energy Systems: Analysis and Design, McGraw-Hill Education, New York.
Singh, R. , Saini, R. , and Saini, J. , 2006, “ Nusselt Number and Friction Factor Correlations for Packed Bed Solar Energy Storage System Having Large Sized Elements of Different Shapes,” Sol. Energy, 80(7), pp. 760–771.
Bell, I. H. , Quoilin, S. , Wronski, J. , and Lemort, V. , 2013, “ CoolProp: An Open-Source Reference-Quality Thermophysical Property Library,” ASME ORC Second International Seminar on ORC Power Systems, Rotterdam, The Netherlands, Oct. 7–8, pp. 2498–2508.
Sinnott, R. K. , 2009, Chemical Engineering Design: SI Edition, Elsevier, Oxford, UK.
Benato, A. , Kaern, M. , Pierobon, L. , Stoppato, A. , and Haglind, F. , 2015, “ Analysis of Hot Spots in Boilers of Organic Rankine Cycles Units During Transient Operation,” Appl. Energy, 151, pp. 119–131.
Pezzuolo, A. , Benato, A. , Stoppato, A. , and Mirandola, A. , 2016, “ The ORC-PD: A Versatile Tool for Fluid Selection and Organic Rankine Cycle Unit Design,” Energy, 102, pp. 605–620.
Benato, A. , 2017, “ Performance and Cost Evaluation of an Innovative Pumped Thermal Electricity Storage Power System,” Energy, 138, pp. 419–436.
Zhang, H. , Baeyens, J. , Cáceres, G. , Degrève, J. , and Lv, Y. , 2016, “ Thermal Energy Storage: Recent Developments and Practical Aspects,” Prog. Energy Combust. Sci., 53, pp. 1–40.

## Figures

Fig. 1

Sketch of the PTES system proposed in Ref. [15]

Fig. 2

Layout of the new PTES during charging phase

Fig. 3

Layout of the new PTES during delivery phase

Fig. 4

Scheme of the packed bed and its element “m

Fig. 5

Charge: trends of the layers' temperature

Fig. 6

Discharge: trends of the layers' temperature

Fig. 7

First and last layer temperature trends during two charge/discharge cycles

Fig. 8

Trends of the power in the plant components during charge and delivery

## Tables

Table 1 Bed materials characteristics
Table 2 Charge/discharge time, round-trip efficiency, energy stored, and plant cost versus bed material

## Discussions

Some tools below are only available to our subscribers or users with an online account.

### Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related Proceedings Articles
Related eBook Content
Topic Collections