Development and evaluation of a new hybrid ammonia fuel cell system with solar energy

Energy 189 (2019) 116185

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Energy journal homepage: www.elsevier.com/locate/energy

Development and evaluation of a new hybrid ammonia fuel cell system with solar energy O. Siddiqui a, *, I. Dincer a, b a

Clean Energy Research Laboratory, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario, L1H 7K4, Canada b Faculty of Mechanical Engineering, Yildiz Technical University, Istanbul, Turkey

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 February 2019 Received in revised form 18 September 2019 Accepted 21 September 2019 Available online 24 September 2019

In this study, a novel hybrid thermal energy storage and ammonia fuel cell system is developed and investigated for a solar tower based power plant. An annual analysis of the developed system is performed by considering the monthly average days. Also, the actual power demands as well as the solar intensity changes are taken into account. Thermodynamic approaches of energy and exergy analyses are utilized for system analysis. The energetic efficiency of the proposed power plant varies between 5.3% and 37% while the exergy efficiency ranges between 5.7% and 39%, depending on the corresponding power demands as well as available solar energy. The system simulation results for each month are also described in terms of the specific exergies and enthalpies at the turbine inlets. Furthermore, energy efficiency of the direct ammonia fuel cell is evaluated to be 37% and the exergy efficiency is found to be 34% at the peak power density. At a temperature of 500
C, a specific thermal energy storage capacity of 266 kJ kg1 is determined for the hybrid system. © 2019 Elsevier Ltd. All rights reserved.

Keywords: Solar energy Ammonia Ammonia fuel cell Energy storage Energy Exergy Efficiency

1. Introduction Energy production in an environmentally-benign way certainly remains a central aim for several states globally. Especially, in this era, where the global demand for energy is estimated to increase by nearly 50% by 2030 [1], concerns are on the rise internationally. Considerable quantities of fossil fuels are presently consumed to provide for the needs of energy across the globe. Nearly 80% of the consumption of energy globally constitutes of fossil fuel resources [2]. Such this continuous and massive fossil fuel consumption has deteriorated the environment significantly. Various global organizations have been advocating and trying to decrease this fossil fuel dependence, and solar energy is in this regard expected to play a central role. Moreover, several other clean fuels are currently investigated, and hydrogen is one of the favorable options as it does not result in detrimental emissions when used for energy production. Also, hydrogen is associated with exceptional energy carriage properties owing to its high energy density. However,

* Corresponding author. E-mail addresses: [email protected] (O. Siddiqui), ibrahim. [email protected] (I. Dincer). https://doi.org/10.1016/j.energy.2019.116185 0360-5442/© 2019 Elsevier Ltd. All rights reserved.

hydrogen entails a low volumetric density, making it difficult to store or transport. Furthermore, hydrogen entails various safety issues owing to its odorless appearance along with high flammability. To overcome the challenges associated with hydrogen, storing hydrogen through chemical means has attracted increased interest. Owing to several favorable properties, ammonia is recognized as a promising candidate. Furthermore, it is considered a fuel that is free of carbon atoms and is one of the most commonly produced chemical [3]. In addition to this, to develop an energy infrastructure that is environmentally benign and sustainable, it is essential to enhance the performances of clean energy resources such as solar power generation systems with thermal energy storage and ammonia fuel cell systems. Several studies have been conducted on such power generation systems. Different direct ammonia fuel cell (DAFC) technologies were studied in the recent past. Most of the past studies were focused on solid oxide electrolyte based ammonia fuel cells [4e17]. These type of fuel cells entail the usage of a thin electrolyte that is functional at high temperatures generally ranging between 550
C and 800
C. However, few studies have been reported on molten alkaline electrolyte DAFC. Yang et al. [18] studied DAFC entailing direct ammonia fuel input type arrangement with molten potassium and sodium hydroxide salts. Also, the

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O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

electrode was based of platinum material. The temperature range they utilized was between 200
C and 220
C. The power density achieved at the peak point was 16 mW cm2 and 10.5 mW cm2. These were achieved at 220
C and 200
C respective operating temperatures. Furthermore, Ganley [19] also studied direct ammonia fuel cell entailing a molten electrolyte. They used molten potassium and sodium hydroxide salt mixtures. The developed fuel cell was tested at various temperatures (200oCe450
C). A power density of 16 mW cm2 was recorded at the maximum point at a 200
C molten salt temperature. Moreover, at a higher temperature of 450
C, the power density at the maximum value was found to be 40 mW cm2, respectively. The possibility of utilizing molten salt electrolyte in DAFC technologies opens a wide range of new opportunities to increase the overall performances of energy systems. Specifically, in the case of molten salt thermal energy storage (TES) systems used in solar energy based power plants. The TES systems are utilized to store the excess amount of energy during the day that can be used later in the absence of solar energy. TES systems are considered vital in overcoming the intermittent nature of solar energy. During periods of excess available energy, the TES system is charged with thermal energy. Later, when solar energy is not available or sufficient, the TES system is discharged to extract the stored thermal energy. Several studies have been conducted on molten salt TES systems for solar energy applications. Zhao et al. [20] designed and investigated a solar thermal energy system integrated with a molten salt TES system for residential heating. A sample house located in Melbourne was utilized for system modelling and simulation. Different weathers of the year were investigated. The designed system was found capable of operating in a consistent manner during night hours. Yang et al. [21] performed an investigation of operation cycling of a molten salt TES system. They utilized a finite volume methodology and investigated the temperature distributions as well as efficiencies. It was concluded from their study that lower Reynolds numbers for the melt would result in higher efficiencies. Ozlu and Dincer [22] developed and investigated an integrated energy system with a TES subsystem. The overall system was analysed thermodynamically to investigate its performance. The multigeneration system was designed to produce hydrogen, fresh water, heat and electricity. They found a peak energy efficiency of 36% and exergy efficiency of 44%. Demir and Dincer [23] designed a solar energy based system with a TES subsystem that produces fresh water as well as electricity. A steam Rankine cycle was utilized for power generation and a flash distillation system with multiple stages was used for fresh water production. During the day, solar energy was utilized to operate the system. However, in the absence of sunlight, the molten salt TES was used to supply the required energy to the system. They found overall energy and exergy efficiencies of 19.9% and 46.5% respectively. Various other studies on molten salt TES systems have considered different aspects including transient modelling and optimization, new types of molten salt materials and their enhancements [24e28]. Although previous studies have separately investigated solar thermal power plants and ammonia fuel cells. There is a need to develop new systems that can enhance the energetic and exergetic performances of solar power plants as well as direct ammonia fuel cells. System integration is a vital technique that can improve the efficiencies of various energy production technologies. Hence, in this study, we design and analyse a novel energy storage system for a solar energy based power plant that also entails a DAFC system. A hybrid thermal energy storage and ammonia fuel cell system is proposed that provides both thermal as well as electrical energy when required. The system performance is investigated thermodynamically through energy and exergy analyses. The specific objectives of this study are: (i) to develop, model and simulate a solar

energy based power plant with a hybrid thermal energy storage and ammonia fuel cell (ii) to analyse the performance of the developed system via exergetic and energetic analyses, (iii) to determine the annual average overall efficiencies, (iv) to assess and evaluate the ammonia fuel cell performance by determining the efficiencies at varying temperatures. 2. System description The present study proposes a concentrated solar power generation system equipped with a novel energy storage system that also incorporates an ammonia fuel cell system. The schematic of the proposed system is shown in Fig. 1. Solar radiation from the sun is reflected by arrays of heliostat mirrors to the central receiver. The energy is received at the central solar tower by the heat transfer fluid (Therminol® 66). The heat transfer fluid then transfers the required heat to the Rankine cycle entailing reheat mechanism to generate the required power. In addition to this, the excess amount of energy received is stored in a thermal energy storage system. A new system is proposed that is utilized as both a thermal energy storage as well as an ammonia fuel cell. The hybrid system comprises of a molten salt mixture of sodium and potassium hydroxide. During periods of high available solar radiation, the excess amount of energy is stored in the molten salt mixture by raising its temperature between specified limits. Further, as the molten salt mixture entails an alkaline nature, it is also utilized to generate power by the passage of ammonia fuel through the operation of an alkaline electrolyte based direct ammonia fuel cell. Hence, during the discharging phase, the hybrid system is utilized to extract thermal energy as well as electrical energy. The system is designed considering the solar radiation intensities in the province of Ontario, Canada. An annual solar data analysis is conducted on the system to incorporate the variations in solar radiation throughout the year. Furthermore, the actual energy demands of Ontario are utilized in the design and analysis of the developed system. The system algorithm is designed to produce power according to the necessary power demand at any given hour of the day. Hence, the total turbine and ammonia fuel cell power outputs are equal to the power demand at any given instant. The average days of each month have been taken to conduct an annual analysis. Thus, the actual power demands on these days are taken from Ref. [31] for a community of 100000 people and the solar intensity is also investigated at these days. The system proposed is designed to meet the power demands throughout the year, hence, the lowest solar radiation intensity occurring in the winter month is utilized to determine the heliostat area required. A multi-stage reheat steam Rankine cycle is utilized for power generation. Superheated steam at 1100 kPa enters turbine 1 (T1) at state 3 as depicted in Fig. 1. After leaving T1, it is reheated to a higher temperature of state 3 at a pressure of 740 kPa. In this thermodynamic superheated state, it enters turbine 2 (T2) at state 5. Furthermore, after leaving T2, it is allowed to be reheated again before entering the turbine 3. This occurs at a pressure of 380 kPa at which it enters turbine 3 (T3) at state 7. Saturated water exits T3 at a pressure of 20 kPa. It then passes through a condenser to reject heat and reach the initial state 1 before entering the pump. The temperatures and enthalpies at each state vary with the required turbine power output and the absorbed thermal energy from heat exchanger 1 (HX 1). 3. Thermodynamic analyses In order to analyse the developed system, solar radiation intensities in the province of Ontario, Canada are utilized. As the available solar radiation intensities vary during the year, an annual

O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

3

Fig. 1. Schematic representing the novel hybrid ammonia fuel cell and thermal energy storage system for a solar energy based power plant.

solar data analysis is conducted considering the average day of each month.

(2)

The total solar energy received by the central receiver between sunrise (SR) and sunset (SS) can be evaluated as

3.1. Solar radiation modelling The incident solar radiation on a particular day and time on the heliostat field can be evaluated as

Q_ s;in ¼ I_b Ahef

Q_ rec ¼ I_b Ahef Jhef

(1)

where the beam radiation intensity is denoted by I_b and the total heliostat field area is represented by Ahef . The incident solar energy on the heliostat field is reflected on to the central receiver. Considering a heliostat field efficiency (Jhef )of 80% and negligible energy losses at the central tower receiver [29], the amount of solar energy received is evaluated as

SS ð

Qrec;day ¼

Q_ rec dt

(2a)

SR

The beam radiation intensity for a particular location, day and time can be determined as

I_b ¼ cosqz I_n

(3)

In the above equation, I_n denotes the normal radiation intensity that is evaluated as [29].

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O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

I_n ¼ 0:9715Eo I_sc tr to tg tw ta

(4)

where the solar constant is represented by I_sc and the scattering transmittances including gas, aerosols, water, ozone and Rayleigh are denoted by tg ; ta ; tw ; to ; tR respectively. Furthermore, Eo denotes the eccentricity factor that can be written in the form:

Eo ¼ 1:00011 þ 0:034221cosD þ 0:00128sinD þ 0:000719cos2D þ 0:000077sin2D (5) The parameter cosqz in Eq. (3) can be evaluated as

cosqz ¼ cosdcosfcosu þ sindsinf

(6)

where the hour angle is denoted by u, the declination angle of the sun is represented by d, the zenith angle is denoted by qz and the latitude is represented with f. The hour angle u is derived from the local solar time as

u ¼ 15ð12  STÞ

(7)

Vact ¼

  RT j ln j0 anF

(14)

In the above equation, the temperature is denoted by T, the current density and exchange current density are represented by j and j0 respectively and the transfer coefficient is represented by a. The polarization loss in the fuel cell arising due to the presence of mass transport limitations is known as concentration polarization that is evaluated as

Vconc ¼

  RT j ln L anF jL j

(15)

Here, the limiting current density is represented by jL. Furthermore, the Ohmic losses in the fuel cell need to be considered that take into account the ionic as well as electronic resistances of the cell components. The Ohmic losses can be evaluated as

VOhmic ¼ RFC J

(16)

where the Ohmic resistance is denoted by RFC and J represents the current density. The fuel cell voltage is evaluated by considering these losses as

VFC ¼ E  Vact  Vconc  VOhmic 3.2. Ammonia fuel cell modelling The electrical energy output obtained from the ammonia fuel _ ) is a result of electrochemical reactions occurcell operation (W FC ring within the cell. Ammonia gas is entered at the anode, where the electrochemical reaction occurs with hydroxyl ions present in molten salt alkaline electrolyte. The anodic reaction can be represented as

2NH3 þ 6OH /N2 þ 6H2 O þ 6e



(9)

The overall reaction for the ammonia fuel cell is denoted as

2NH3 þ 1:5O2 /N2 þ 3H2 O

(10)

From the overall reaction, it is possible to evaluate the reversible potential at standard conditions:

Estd rev ¼ 

DG

DG ¼ DH  T DS

(12)

The theoretical voltage for the ammonia fuel cell can be evaluated at different partial pressures and temperatures from:

RT ln þ 6F

_ ¼h W FC DCAC VFC jA

(18)

_ In the above equation, W FC denotes the AC power output from the fuel cell. The converter (DC to AC) efficiency is denoted by hDCAC and A is the cell area.

3.3. Energy and exergy analyses The developed system is analysed and its performance is investigated through thermodynamic analyses approaches of energy and exergy. These are employed on all components of the developed system to investigate their energetic and exergetic performance and to evaluate the overall system energy efficiency and exergy efficiency. In the thermodynamic analysis, 298 K is taken as the reference environment temperature and 101 kPa is considered as the ambient pressure. Furthermore, adiabatic operation of the pump and turbines is considered. In addition, negligible changes in

(11)

nF

where n denotes the number of electrons, the Faraday’s constant is expressed by F and DG represents the Gibbs function that is evaluated as:

E ¼ Estd rev

Table 2 lists the utilized parameters and operating conditions for the fuel cell modelling. The AC electrical power output from the fuel cell is determined as

(8)

Furthermore, the cathode side of the cell entails the electrochemical between O2 and H2O molecules required to complete the half-cell cathodic reaction denoted as

1:5O2 þ 3H2 O þ 6e/6OH

(17)

" 2  1:5 # PNH3 PO2  3   PH2 O PN2

(13)

where T represents the temperature and p denotes the partial pressure. When the fuel cell is operated, several polarization losses arise that lower the cell voltage. The first type of polarization loss is termed as activation polarization that can be evaluated as

Table 1 Important system parameters and operating conditions. Parameter

Value

Number of heliostats Heliostat mirror Efficiency of heliostat field Heat transfer fluid Latitude Longitude Molten salt Molten salt mixture mass ratio Mass of MSS Minimum MSS temperature Isentropic efficiency of pumps and turbines Steam turbine T1 inlet pressure Steam turbine T2 inlet pressure Steam turbine T3 inlet pressure Condenser pressure Percentage of load covered by AFC

49587 11 m  11 m 80% Therminol® 66 51.2538 85.3233 KOH þ NaOH 1:1 (KOH:NaOH) 49.4 kt 300
C 85% 1100 kPa 740 kPa 380 kPa 20 kPa 10%

O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

5

Table 2 Molten alkaline electrolyte based direct ammonia fuel cell modelling parameters and operating conditions. Parameter

Value

Alkaline electrolyte Ohmic Resistance Exchange current density Limiting current density Electrode area Number of cells Mass of molten salt Operating temperature range

Molten KOH þ NaOH 0.56 U cm (at 500
C) - 0.79 U cm (at 300
C) 0.37 A m2 8000 A m2 (at 300
C) e 10000 A m2 (at 500
C) 100 m2 20 49.4 kt 300
Ce500
C

(Source [32e34])

the potential as well as kinetic energies are assumed and negligible pressure losses are considered. Also, the isentropic efficiency of the pump as well as the turbines is considered to be 85% [30]. The mass balance equation for a general control volume can be derived from the principle of conservation of mass and can be expressed as the following:

electrolyte ammonia fuel cell allows the production of eletrical energy. For the charging phase of the TES, the energy balance equation is expressed as

X X dmcv m_ i  m_ e ¼ dt e i

mMS u1MS þ

(19)

Here, the equation for energy balance of a general control volume can be derived from the first law of thermodynamics and can be expressed as the following:

_ þ Q_  W

X m_ i hi þ i

V 2i 2

! þ gZi



X m_ e he þ e

V 2e 2

! þ gZe

¼

dEcv dt (20)

Note that irreversibilities in a given process lead to entropy generation. The equation for the entropy generation rate of a general control volume is denoted as

X X Q_ dScv X k þ S_gen ¼ m_ e se  m_ i si  dt Tk e i

Each system component is analysed energetically and exergetically. The energy balance equation for the central solar tower receiver is denoted as SS ð

m_ S3 hS3 dt þ

SR

Q_ rec dt ¼

SR

SS ð

m_ S1 hS1 dt

(23)

SR

where SR and SS denote sunrise and sunset respectively. Similarly, the entropy balance equation is implemented as SðS

SR

m_ S3 sS3 dt þ

SðS

SR

SðS SðS Q_ rec dt þ S_gen:rec dt ¼ m_ S1 sS1 dt Trec SR

(24)

SR

m_ S3 exS3 dt þ

SðS

SR

_ Q_ rec dt ¼ Ex

SðS

SR

m_ S1 exS1 dt þ

tðch

mMS s1MS þ

tðch Q_ ch dt þ S_gen;TES;ch dt ¼ mMS s2MS T

0

(27)

0

The equation denoting the exergy balance for the charging period of the TES is written as tðch

mMS ex1MS þ

_ Q_ ch dt ¼ m ex Ex MS 2MS þ

0

tðch

_ Ex dest;TES;ch dt

(28)

0

The time for which the TES is charged (tch Þ is a function of the power demand and the available solar energy on a particular day. Furthermore, the amount of heat rate flow to the TES during charging phase is a function of the surplus power available after meeting the demand. When the available solar energy reduces to a value lower than the power demand at a given time, the discharging phase is initiated. During the discharging phase, the novel hybrid system allows discharging of thermal energy as well as electrical energy. The thermal energy is discharged and transferred to the multi-stage reheat Rankine cycle via heat exchanger 1 (HX 1). Further, electrical energy is produced from the ammonia fuel cell operation as described earlier. The energy balance for the hybrid system for the discharging phase can be expressed as tð dis

SðS

(26)

The equation for the entropy balance for the charging phase can be written as

SR

mMS u3MS þ

and the exergy balance equation is denoted as SðS

Q_ ch dt ¼ mMS u2MS

0

(21)

k

SS ð

tðch

m_ NH3 hNH3 þ m_ O2 hO2 dt

0

_ Ex d;CR dt

(25)

tð dis

¼ mMS u4MS þ

SR

Furthermore, for the analysis of the hybrid ammonia fuel cell and TES system, different phases including charging, discharging and storage need to be considered. During the charging phase, thermal energy is transferred to the hybrid system. However, during the discharging phase, both thermal energy as well as electrical energy is extracted from the hybrid system. The molten alkaline

0 tð dis

þ

_ dt W FC

m_ N2 hN2 þ m_ H2 Oe hH2 Oe dt þ

tð dis

Q_ dis dt

0

(29)

0

The equation for the entropy balance for the discharging phase can be written as

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O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

tð dis

mMS ex3MS þ

m_ NH3 exNH3 þ m_ O2 exO2 dt

0 tð dis

mMS s3MS þ

m_ NH3 sNH3 þ m_ O2 sO2 dt þ

tð dis

tð dis

S_gen;TES;dis

¼ mMS ex4MS þ 0

o

0 tð dis

¼ mMS s4MS þ 0

m_ N2 sN2 þ m_ H2 Oe sH2 Oe dt þ

m_ N2 exN2 þ m_ H2 Oe exH2 Oe dt þ

tð dis

Q_ dis dt T

tð dis

(30)

0

The equation denoting the exergy balance for the discharging period of the TES is written as

þ 0

_ dt þ W FC

tð dis

_ Q_ dis dt Ex

0 tð dis

_ Ex dest;TES;dis dt

0

(31) The energy balance equation can be expressed for the heat

Fig. 2. Schematic showing the algorithm for the design and analysis of the developed system.

O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

exchanger (HX 1) transferring heat to the multi-stage Rankine cycle for a given day as

ð

m_ S1 hS1 þ m_ 2 h2 þ m_ 4 h4 þ m_ 6 h6 dt ¼

ð

m_ S2 hS2 þ m_ 3 h3 þ m_ 5 h5

þ m_ 7 h7 dt

ð

ð

The entropy balance equation can be expressed for HX 1 as

ð

m_ S1 sS1 þ m_ 2 s2 þ m_ 4 s4 þ m_ 6 s6 dt þ S_genHX1 dt ð ¼ m_ S2 sS2 þ m_ 3 s3 þ m_ 5 s5 þ m_ 7 s7 dt

ð

m_ S1 exS1 þ m_ 2 ex2 þ m_ 4 ex4 þ m_ 6 ex6 dt ¼ ð _ þ m_ 5 ex5 þ m_ 7 ex7 dt þ Ex dest;HX1 dt

ð

(33)

m_ S2 exS2 þ m_ 3 ex3

ð

ð _ dt m_ 4 h4 dt þ W T1

(35)

_ where the work output W T1 is a function of the power demand. Similarly, the entropy balance equation for T1 is implemented as

ð

m_ 3 s3 dt þ

ð

S_gen:T1 dt ¼

ð

m_ 4 s4 dt

(36)

and the exergy balance can be applied on T1 as

ð

m_ 3 ex3 dt ¼

ð

ð ð _ dt þ Ex _ m_ 4 ex4 dt þ W T1 d;T1 dt

(37)

Similarly, the energy balance equation for T2 can be written as follows:

ð

m_ 5 h5 dt ¼

ð

ð _ dt m_ 6 h6 dt þ W T2

(38)

where the above parameters are also a function of the power demand. The entropy balance equation for T2 is implemented as

ð

m_ 5 s5 dt þ

ð

S_gen:T2 dt ¼

ð

m_ 6 s6 dt

(39)

m_ 5 ex5 dt ¼

ð

ð ð _ dt þ Ex _ m_ 6 ex6 dt þ W T2 d;T2 dt

m_ 8 h8 dt ¼

ð

ð

m_ 1 h1 dt þ Q_ con dt

(41)

The entropy balance equation for the condenser can be written as

m_ 8 ex8 dt ¼

m_ 1 h1 dt þ

m_ 1 s1 dt þ

ð

ð

ð

m_ 1 ex1 dt þ

(42)

ð ð _ Q_ con dt þ Ex _ m_ 1 ex1 dt þ Ex d;con dt

(43)

_ pump dt ¼ W

ð

m_ 2 h2 dt

(44)

S_gen:pump dt ¼

ð

m_ 2 s2 dt

(45)

ð

_ pump dt ¼ W

ð

m_ 2 ex2 dt þ

ð

_ Ex d;pump dt



(46)

The algorithm depicting the methodology pursued in this study for modelling and simulating the overall system and associated subsystems is shown in Fig. 2. The first procedure involves checking the availability of solar insolation. In the absence of solar insolation (sunset hours), the energy stored in the novel hybrid TES system during periods of excess power is utilized to meet the power demand. This includes transferring the thermal energy from the TES to the multi-stage reheat Rankine cycle via HX1. In addition, the ammonia fuel cell (AFC) is operated during the discharging phase to generate power electrochemically as described earlier. However, when there is presence of solar insolation, the next procedure involves the calculation of the received solar energy by the solar tower. Next, the demand at that particular instant is checked to determine if the incoming solar energy is sufficient. If it is sufficient, the power demand is met via the multi-stage reheat Rankine cycle and the availability of any excess power is assessed. In case of any excess available power, it is stored in the hybrid TES system for later usage. In case when the incoming solar energy is insufficient, the power shortage is met by discharging the hybrid TES system. The operating parameters, specifications and properties used for the solar tower and ammonia fuel cell simulation and analysis are listed in Tables 1 and 2. The number of heliostats are determined according to the heliostat field area required to meet the power demands during the months with the least available solar radiation.

3.4. Efficiencies

(40)

The balance equations are implemented for T3 in a similar way as described above for T1 and T2. For the condenser, the energy balance equation is also a function of the power demand and can be expressed for a given day as follows:

ð

ð _ Q con dt Tcon

The energy and exergy efficiency of the fuel cell system at a given current density is evaluated as

and the exergy balance equation for T2 is denoted as

ð

m_ 1 s1 dt þ

Similarly, the entropy balance equation for pump is denoted as

ð

ð

Here, the energy balance equation for turbine 1 (T1) is expressed as the following:

m_ 3 h3 dt ¼

ð

and the exergy balance equation is expressed as

(34)

ð

S_gen:con dt ¼

For the pump, the energetic balance can be denoted as

ð

The exergy balance equation for HX 1 is expressed as follows for a given day:

ð

and the exergy balance equation is denoted as

(32) ð

m_ 8 s8 dt þ

7

hFC ¼

P_ d A n_ NH3 LHV

(47)

jFC ¼

P_ d A n_ NH3 ex

(48)

where P_ d denotes the power density, n_ NH3 represents the ammonia flow rate, A denotes the active cell area, specific exergy of ammonia is denoted by ex and the lower heating value is represented by LHV. The ammonia flow rate can be evaluated as

8

O. Siddiqui, I. Dincer / Energy 189 (2019) 116185

ð

n_ NH3 ¼

ð ð ð _ dt þ W _ dt þ W _ dt þ W _ W T1 T2 T3 FC dt ð ð jov ¼ _ Q_ s;in dt þ n_ Ex NH3 exNH3 dt

JA ne F

(51)

(49)

in Eq. (38), J represents the current density, ne represents the number of transferred electrons in moles and the Faraday’s constant is denoted by F. The average energy efficiency of the overall system is determined as

_ T denotes the turbine work output, W _ where W FC represents the fuel cell power output, n_ NH3 denotes the ammonia input flow rate, LHVNH3 and exNH3 denote the lower heating value and specific exergy of ammonia, Q_ s;in denotes the incident solar radiation on the _ Q_ s;in represents the exergy associated with the heliostat field and Ex incident solar radiation. 4. Results and discussion

ð

ð ð ð _ T dt þ W _ T dt þ W _ T dt þ W _ W FC dt 1 2 3 ð ð hov ¼ Q_ s;in dt þ n_ NH3 LHVNH3 dt

(50)

The average exergy efficiency of the overall system is evaluated as

The engineering equation solver (EES) software is utilized to obtain the thermodynamic properties and perform the system simulation and analysis [35]. The actual power demands for 100000 people in the province of Ontario, Canada on the monthly average day are considered [31]. The calculation conditions and input parameters employed in the simulation and modelling are summarized in Tables 1 and 2 The overall energy efficiency of the

800

Beam radiation (W m-2)

700 600

Jan

Feb

March

April

May

June

500 400 300 200 100 0 1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour 700

Beam radiation (W m-2)

600

500

July

Aug

Sep

Oct

Nov

Dec

400

300

200

100

0 1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour Fig. 3. Direct normal irradiance on the average day of each month in Ontario.

O. Siddiqui, I. Dincer / Energy 189 (2019) 116185 1.4

3500

V_300 T=300oC V_400 T=400oC

1.2

3000

2500

0.8

2000

0.6

1500

0.4

1000

0.2

500

0 0

2000

4000

6000

8000

Power density (W m-2)

Voltage (V)

V_500 T=500oC 1

0 10000

9

day of each month is depicted in Fig. 3. These are important for the design of the developed system. The range of solar irradiation found to occur in the month of June is between 0 and 671.1 W m2. The peak solar radiation intensities are found to vary considerably during the year. For instance, the least solar radiation intensity at the peak value is determined to occur in the month of December at the value of 219.1 W m2. Furthermore, as can be depicted from Fig. 3, the number of daylight hours also vary significantly. The minimum daylight hours are entailed with the month of December of 8 h. These increase as the summer months are approached. 4.1. Performance assessment of the hybrid TES and DAFC system

Current density (A m-2)

Fig. 4. Polarization graphs and power density vs current density graphs for the molten alkaline electrolyte direct ammonia fuel cell at varying temperatures.

developed system is found to be in the range of 5.3%e37%, according to the month of the year and the corresponding energy demands. Moreover, the exergetic efficiency of the proposed system throughout the year is determined to be between 5.7% and 39%. The evaluated direct normal irradiance for Ontario on the average

The polarization curves as well as the power density vs current density results obtained for the ammonia fuel cell system are depicted in Fig. 4. The temperatures of the hybrid TES and fuel cell system effect the peak power densities. At a temperature of 300
C, the peak power density is evaluated to be 2586 W m2. However, at a higher temperature of 400
C and 500
C, the peak power densities increase to 2698 W m2 and 2896 W m2 respectively. Hence, it is recommended to utilize the optimum temperature ranges of operation. Also, these peak power densities are observed to lie in the current density range of 5225 A m2 to 6481 A m2.

a

1 0.9

Ener_300 T=300oC

Energy efficiency

0.8 Ener_400 T=400oC

0.7

o

T=500 C Ener_500

0.6 0.5 0.4 0.3 0.2 0.1 0 0

2000

4000

6000

8000

10000

Current density (A m-2)

1

b

0.9

Exergy efficiency

0.8

T=300oC Exer_300

T=500oC Exer_500

Exer_400 T=400o

C

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0

2000

4000

6000

8000

10000

12000

Current density (A m-2) Fig. 5. (a) Energy efficiency vs current density and (b) exergy efficiency vs current density results for the molten alkaline electrolyte direct ammonia fuel cell.

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Specific heat storage (kJ/kg)

300

250

200

150

100

50

0 300

350

400

Temperature (oC)

450

500

Fig. 6. Heat storage in the molten salt thermal energy storage system per unit mass of salt (50 wt% NaOHþ50 wt% KOH) with an increase in temperature utilizing 300
C as the minimum temperature.

Furthermore, the effect of temperature on the efficiencies of the ammonia fuel cell system at varying current densities is depicted in Fig. 5 (a) and (b) respectively. The energy efficiency is evaluated to be 37% and the exergy efficiency is determined to be 34% assessed at the maximum power density with an operating temperature of 300
C. However, the energy and exergy efficiencies at the peak power densities are observed to decrease with increasing temperatures. The energy efficiency at the peak power density at a temperature of 500
C is observed to decrease to 34% at the peak power density value. Similar trends are observed for the exergy efficiencies. At higher cell temperatures, the drop in efficiencies may be attributed to greater number of molecules required owing to larger current densities at the peak power density values. Further, the increase in power densities with increasing temperatures can be attributed to lower polarization voltage losses at higher temperatures. Hence, it is recommended to set the operating point of the fuel cell such that it provides the required amount of power output as well as high efficiencies at varying temperatures. The operating temperatures also effect the thermal energy storage. The specific thermal energy storage capacity of the hybrid system as a function of temperature is depicted in Fig. 6. The minimum temperature of the molten salt based hybrid system is considered to be 300
C. As can be depicted from the figure, at a molten salt temperature of 500
C, a specific thermal energy storage capacity of 266 kJ kg1 is obtained. However, further studies should be conducted to analyse the effects of electrolyte temperature on the electrochemical behaviour of the NaOH and KOH mixture. 4.2. Results of dynamic modelling and simulation The simulation results of the total turbine power output as well as the ammonia fuel cell power output are depicted in Fig. 7 (a)-(c). Fig. 7 (a) shows the results for the average days of the months of January to April, Fig. 6 (7) depicts the results for May to August and Fig. 7 (c) depicts the results for September to December. During January to April, the highest total turbine power output is evaluated for the month of February of 131.42 MW. This is attributed to the peak power demand at the specific average day of the month. The corresponding ammonia fuel cell power output is 14.6 MW. Furthermore, for the period of May to August, the maximum plant turbine power output of 136.2 MW is obtained in August and the

Fig. 7. Simulation results showing the total turbine power output and AFC power output on the average days of (a) JaneApril, (b) MayeAug and (c) SepeDec.

corresponding fuel cell power output is evaluated as 15.1 MW. In the September to December period, the peak turbine power output of the plant is evaluated as 125.2 MW for the month of December with a corresponding fuel cell power output of 13.9 MW. Similarly, the lowest turbine peak power outputs are found in the months of April, May and October. In addition to this, as can be depicted from

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Fig. 6, the operation time of ammonia fuel cell varies for each month. This depends on the daylight hours on the specific days. The ammonia fuel cell is operated only when there is no sunlight or the available sunlight is insufficient. These simulation results however are evaluated for the power demands in Ontario for the year 2016 and can vary for different years. Nevertheless, the trends are expected to remain the same. Furthermore, the simulation results depicting the specific enthalpies and specific exergies at the turbine inlets are depicted in Figs. 8e11. In Fig. 8 (a), the results January are depicted. The peak specific enthalpy and exergy values are observed to be at state 7 that corresponds to the Turbine 3 inlet. The specific enthalpy at this peak point of operation is found to be 9147 kJ kg1 and the corresponding specific exergy is evaluated as

11

5685 kJ kg1. The Turbine 1 inlet enthalpies and exergies are found to be comparatively lower than Turbines 2 and 3. The specific enthalpy and exergy vary between 2505 and 3403 kJ kg1 and 787e1136 kJ kg1 at the Turbine 1 inlet. Similarly, the simulation results of February and March are shown in Fig. 8 (b) and (c). In February, the specific enthalpies and exergies are evaluated to be in the range 7088e9409 kJ kg1 and 3797e5920 kJ kg1. However, in March the peak enthalpy value reduced to 8104 kJ kg1 that occurred at the Turbine 3 inlet in the 20th hour of the day. Moreover, Fig. 9 depicts the results for the months of AprileJune. In this period, a peak enthalpy of 8410 kJ kg1 is found to be achieved in the month of June at the inlet of Turbine 3. Also, the corresponding peak specific exergy is determined to be 5028 kJ kg1. This peak

a

b

c Fig. 8. Simulation results showing the specific enthalpy and specific exergy at the inlets of T1, T2 and T3 on the average days of (a) Jan, (b) Feb and (c) March.

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a

b

c Fig. 9. Simulation results showing the specific enthalpy and specific exergy at the inlets of T1, T2 and T3 on the average days of (a) April, (b) May and (c) June.

value is attributed to the high power demand at the corresponding point of operation. The specific enthalpy at the inlet of the Turbine 3 (h7) is found to vary from 6174 to 7598 kJ kg1, 5431e7129 kJ kg1 and 5580e8410 kJ kg1 for the months of April, May and June respectively. Fig. 10 shows the results of the months JulyeSeptember. Similar to previous figures, the simulation results of the specific enthalpies and exergies at the inlets of Turbines 1e3 are presented. The enthalpies and exergies at the inlet of Turbine 3 are comparatively higher. The ranges of these inlet enthalpies at state 7 are between 5576 and 8063 kJ kg1, 3889e9693 kJ kg1 and 5836e8291 kJ kg1 respectively for July, August and September. Moreover, Fig. 11 depicts the results of the last three months. The peak specific enthalpy among these months of 8984 kJ kg1 is observed to be achieved in the month of December at the inlet of Turbine 3. Also, the specific exergy at the corresponding operation point is determined as 5539 kJ kg1. The least peak enthalpy is observed for the month of October. The range of the specific enthalpies as well as exergies is a function of the power demands that vary according to the time of day. 4.3. Energy and exergy efficiencies of the overall system The energetic efficiencies and exergetic efficiencies of overall

system evaluated at the monthly average days are shown in Fig. 12. The highest energetic efficiency of 37% is evaluated in the month of December and the highest exergy efficiency is obtained 39% for the same month. However, the least energetic efficiency of 5.4% is found for the month of May and the least exergetic efficiency is found to be 5.7% for the same month. The efficiency values for all other months are also shown in the Figure. The trend observed in the energy and exergy efficiencies is attributed to the design parameters of the power plant utilized. The solar heliostat field area was determined according to the least incoming solar radiation that occurs in the month of December to ensure the plant can operate throughout the year. However, in the month of May, the solar radiation intensities are considerably higher, thus lowering the energetic and exergetic efficiencies as compared to the months with lower solar radiation. Thus, it is recommended to conduct further studies to determine the optimum design parameters that will allow the plant operation with the optimum efficiencies across the year. In addition, further studies should be conducted to investigate and simulate the simultaneous thermal, fluid and electrochemical interactions occurring in the hybrid system.

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a

b

c Fig. 10. Simulation results showing the specific enthalpy and specific exergy at the inlets of T1, T2 and T3 on the average days of (a) July, (b) Aug and (c) Sep.

4.4. Thermal energy savings with the hybrid system The energy output evaluated for the monthly average days for the DAFC is tabulated in Table 3. Further, the thermal energy savings from the TES corresponding to these DAFC power outputs are also listed. These values depict the advantageous characteristics of the hybrid system. The average energy output from the DAFC for each month is listed that corresponds to a thermal energy saving from the TES as steam turbines did not have to be used to generate this energy. The energy savings have been evaluated considering the average efficiencies of each month given in Fig. 12. The highest DAFC energy output is observed to be on the average day of December where an energy output of 214.1 MWh is evaluated. This

is attributed to the low solar availability in this month as can be inferred from Fig. 3. Similarly, the lowest DAFC energy output is evaluated for the month of July owing to the high solar availability, which does not necessitate the operation of the hybrid system. Moreover, the highest amount of energy savings are evaluated for the month of May in which 2196.3 MWh of energy savings are found considering the average efficiency and DAFC energy output. Thus, the proposed system provides an opportunity to utilize thermal energy storage with a more effective technique. 5. Conclusions In this paper, a novel solar tower based power generation

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a

b

c Fig. 11. Simulation results showing the specific enthalpy and specific exergy at the inlets of T1, T2 and T3 on the average days of (a) Oct, (b) Nov and (c) Dec.

system is developed and analysed that incorporates a hybrid ammonia fuel cell and molten salt thermal energy storage system. The performance of the power plant is investigated on the monthly average days to conduct an annual analysis and assessment of the system. Thermodynamic energy and exergy analyses are conducted to determine the energy and exergy efficiencies. Variations in the solar intensity and power demands are considered in the analysis. The energetic efficiency of the proposed system varies between 5.3% and 37% throughout the year, depending on the corresponding

power demands as well as the month of the year. The exergetic efficiency of the proposed system varies between 5.7% and 39%. The energy efficiency and exergy efficiency of the direct ammonia fuel cell is found to be 37% and 34% respectively at the peak power density. The system simulation results for each month are described in terms of the specific enthalpies and exergies at the turbine inlets. Further studies on the development of solar based systems with the proposed hybrid energy storage system should be investigated experimentally. Also, an economic and environmental

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LHV m_ n_ P Q Q_ R R ST s S t T u V _ W

u Z

molar lower heating value (kJ mol1) mass flow rate (kg s1) molar rate (mol s1) power density (W m2) heat transfer (kJ) heat transfer rate (kW) resistance (U) universal gas constant solar time (hours) specific entropy (kJ kg1 K1) entropy (kJ K1) time (hours) temperature (oC) specific internal energy (kJ kg1) voltage (V) work rate (W or kW) hour angle (degrees) zentih

Greek letters energy efficiency exergy efficiency heliostat efficiency transfer coefficient

h j J a

Fig. 12. The results of energy and exergy efficiencies for each month.

Table 3 Average DAFC energy outputs and the corresponding thermal energy savings for the average day of each month. Month

DAFC output (MWh)

Thermal energy savings (MWh)

Jan Feb March April May June July Aug Sep Oct Nov Dec

203.6 202.8 137.8 133.4 118.1 120.6 112.0 176.5 162.5 153.9 183.2 214.1

660.2 1012.2 1249.8 1822.5 2196.3 2146.7 1956.8 2105.0 1724.9 1187.9 763.3 578.6

study of the proposed system is recommended. In addition, other types of moten electrolytes should also be investigated, and the changes in the system performance should be studied. Nomenclature A ex E _ Ex F G h J I_

area (m2) specific exergy (kJ kg1) potential (V) exergy rate (kW) Faraday’s constant Gibbs free energy (kJ) specific enthalpy (kJ kg1) current density (A m2) solar radiation (W m2)

Subscript a act b ch con conc cv dest e ex FC gen hef i L MS n r rec rev ov s st T TES w z

aerosols activation beam charging condenser concentration control volume destroyed exit exergy fuel cell generated heliostat field in limiting molten salt normal Rayleigh received reversible overall solar salt turbine thermal energy storage water zenith

Acronyms DAFC FC HX LHV MS SR SS

direct ammonia fuel cell fuel cell heat exchanger lower heating value molten salt sunrise sunset

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