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Advanced exergoeconomic evaluation of a heat pump food dryer
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
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Advanced exergoeconomic evaluation of a heat pump food dryer Zafer Erbay a,*, Arif Hepbasli b a
Department of Food Engineering, Faculty of Engineering and Natural Sciences, Adana Science and Technology University, 01180 Seyhan, Adana, Turkey b Department of Energy Systems Engineering, Faculty of Engineering, Yas‚ar University, 35100 Bornova, Izmir, Turkey
article info
In this study, the results of conventional and advanced exergoeconomic analyses of the
Article history:
performance of a pilot scale air-source heat pump food dryer were compared for the first
Received 19 March 2014
time. The contributions of the components of the drying system to the exergetic cost
Received in revised form
effectiveness of the dryer were evaluated, and the effects of changing the inlet drying
3 June 2014
temperature were determined. The most important system component was determined to
Accepted 4 June 2014
be the heat recovery unit, followed by the condenser with respect to the reducing poten-
Published online
tials for the total costs of the overall system. Decreasing temperature caused an increase in the cost performance of drying. The modification of the system components for improving
Keywords:
the efficiency of the system can be effectively determined through advanced exer-
Drying
goeconomic approach by stating the realistic potential improvements and the priorities in
Heat pump
the system. © 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
Exergy Exergoeconomics Advanced exergy Advanced exergoeconomy
1.
Introduction
Drying is a notoriously energy-intensive process and its energy consumption value is 10e25% of the total energy consumption in all industries in developed countries, especially for agricultural and food processing sectors that need the high quality requirement of the dried product, often with relatively low thermal efficiency ranging from 25% to 50% (Kudra, 2004; Mujumdar, 2006; Vadivambal & Jayas, 2007). In the context of rising energy prices and growing concerns about climate change and environmental issues, reducing energy consumption and costs in dryers has become a challenging issue (Erbay & Icier, 2010; Minea, 2013).
Heat pumps (HPs) are known to be energy-efficient devices in drying operations because of their heat recovery potential and relatively high energy utilisation efficiencies (Tong, Kozai, Nishioka, & Ohyama, 2010). In HP drying systems, the sensible and latent heat of the evaporated moisture in the drier can be recovered and recycled back to the drier by reheating the dehumidified air (Jangam, 2011). During the past few decades, HP drying systems and their food applications have been very popular due to their low operating cost (Shi et al., 2008; € ylemez, 2006; Zielinska, Zapotoczny, Alves-Filho, Eikevik, So & Blaszczak, 2013). Exergy can be defined in various ways, as presented comprehensively elsewhere (Hepbasli, 2012). According to one commonly used definition, it is the maximum amount of work
* Corresponding author. Tel.: þ90 322 455 0000x2080; fax: þ90 322 455 0009. E-mail addresses: [email protected] (Z. Erbay), [email protected] (A. Hepbasli). http://dx.doi.org/10.1016/j.biosystemseng.2014.06.008 1537-5110/© 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
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Nomenclature c C_ Cp CR CRF E_ F i n P PEC R T top x u U Z_
1
unit exergy cost ($ GJ ) exergy cost rate ($ h1) specific heat (kJ kg1 C1) cost rate () capital recovery factor () exergy rate (kW) function of the independent variables interest rate on capital period of payment (year) pressure (kPa) purchase equipment cost ($) gas constant (kJ kg1 K1) temperature (K or C) time of operation of plant per year (h) independent variable uncertainty in the independent variables uncertainty in the result hourly levelised cost of investment ($ h1)
Greek letters h energy efficiency (%) 3 exergy (second law) efficiency (%) 4 factor of the operating and maintenance cost Superscripts AV avoidable AVEN avoidable-endogenous AVEX avoidable-exogenous EN endogenous EX exogenous REAL experimental operation conditions
that can be produced by a stream of matter, heat or work as it comes to equilibrium with a reference environment. It is also considered as an important and effective tool for analysing, optimising and improving the energy efficiency of the drying systems. With the help of exergy analysis, magnitudes and locations of irreversibilities (exergy destructions) in the system components considered can be successfully specified. However, this information is not enough to create solution-oriented approaches. A relatively new method, the so-called advanced exergy analysis, should be used to reveal the realistic potential and to predict the activities for the system improvements. Exergy destructions of each drying system component are split into their endogenous and exogenous and/or avoidable and unavoidable parts in this method. In addition, splitting the exergy destructions enables the exergy destruction values from a conventional exergy analysis to be understood (Kelly, 2008). Exergoeconomics (thermoeconomics) is the unique combination of exergy analysis with economic constraints to provide the information that cannot be obtained by conventional energy analysis and economic evaluation. The results of exergoeconomic analysis present cost-effective ways for improving the performance of a system (Sahoo, 2008; Morosuk, Tsatsaronis, Boyano, & Gantiva, 2012). Recently, researchers have started to apply the exergoeconomic analysis with advanced exergy methods to the thermal systems and
UN UNEN UNEX
unavoidable unavoidable-endogenous unavoidable-exogenous
Subscripts a air CI capital investment comp compressor cond condenser d destruction dc drying cabinet dd drying ducts elec electrical exp expansion valve ev evaporation evap evaporator f fuel is isentropic k kth component mech mechanical OM operating and maintenance OS overall system p product r refrigerant T total v vapour w work 0 dead state Abbreviations HP heat pump HRU heat recovery unit
obtained invaluable results (Morosuk, Tsatsaronis, & Zhang, 2012; Tsatsaronis & Morosuk, 2009). There have been a few studies conducted on the application of advanced exergy analysis to refrigeration/HP systems (Erbay & Hepbasli, 2013, 2014; Kelly, Tsatsaronis, & Morosuk, 2009; Morosuk & Tsatsaronis, 2008, 2009; Morosuk, Tsatsaronis, & Zhang, 2012), whereas no studies focused on the advanced exergoeconomic analysis of air-source HP drying systems canbe found in the scientific literature, to the best of the authors' knowledge. This provided the prime motivation behind this contribution, which has the objectives to: (i) perform advanced exergoeconomic analysis of a pilot scale HP drying system used in food drying, (ii) evaluate the exergetic cost effectiveness of the drying system in parts, (iii) investigate the effects of the variation of drying temperature on the exergoeconomic performance, and (iv) discuss the performance and improvement potentials of the drying system.
2.
Materials and methods
2.1.
Plums
Freshly harvested plums (Prunus domestica Insititia) were purchased from a local market in the city of Izmir, Turkey. The
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
1a
R407C was used as refrigerant in the HP system. The drying compartment dimensions were 3.0 1.0 1.0 m. The plums were moved by a conveyor band system driven by an electric motor.
V-1
II
2a
3r
2.3.
2r
III
VI
I 1r 3a
4r
IV 5a
7a I III V VII
Compressor Expansion Valve Drying Ducts Heat Recovery Unit
V-2
6a
VII
4a II IV VI
Condenser Evaporator Drying Cabinet
Fig. 1 e The schematic illustration of components of the HP drying system and streams with coded points used in equations of conventional exergy analysis.
purchased plums were cleaned and dipped into 1% NaOH solution for 15 s (Tarhan, 2007). They were then washed with water, and the excess water on the surface of plums removed with a filter paper. They were sliced uniformly (average thickness: 4.0 ± 0.5 mm) and processed within 24 h. The composition of the plum samples was determined to calculate the specific heat values. The moisture, protein, fat, crude fibre and ash contents of plum samples were found using the methods of AOAC (1990) and the composition of the plums used in the calculations of the specific heat of the fresh plum slices were 84.5 ± 1.1%, 0.8 ± 0.1%, 0.2 ± 0.1%, 1.5 ± 0.2% and 0.6 ± 0.1%, respectively. The average final moisture content of the dried plum slices was 10.4 ± 1.5% (wet basis).
2.2.
31
Experimental setup
The plums were dried in a pilot scale HP conveyor dryer, which was designed and constructed in the Department of Mechanical Engineering, Faculty of Engineering, Ege University, Izmir, Turkey (Hepbasli, Erbay, Colak, Hancioglu, & Icier, 2010). The drying system consisted of two main parts; (1) HP, and (2) drying chamber (Fig. 1). The air was heated by an HP system including a scroll compressor, a condenser, an expansion valve, an evaporator and a heat recovery unit (HRU). The air temperature was controlled by a control unit.
Drying procedure and measurements
Before starting the drying processes, the system was run for at least 1 h to obtain steady-state conditions. The plum slices were spread out in a thin layer. The drying experiments were carried out in triplicate at drying air temperatures of 45, 50 and 55 C with a drying air velocity of 1.5 m s1 and a relative humidity of 10%. The drying process continued until the moisture content of the plums reached an equilibrium value. Humidity, temperature and velocity were measured in the drying chamber with robust humidity probes (Testo, 0636.2140, Freiburg, Germany), vane/temperature probes (Testo, 0635.9540, Freiburg, Germany), using professional telescopic handle for plug-in vane probes (Testo, 0430.0941, Freiburg, Germany). The measurements of drying air temperature, velocity and relative humidity were recorded every 5 min. An infrared thermometer (Testo 552-T2, Freiburg, Germany) and a surface thermometer (METEX ME-32, Seoul, South Korea) were used to measure the surface temperatures of the product and the drying chamber walls, respectively. A digital balance (Scaltec SBA 61, Goettingen, Germany) was used to measure the weight loss of the sample during the drying experiments. The ambient temperature and relative humidity were also measured and recorded. The pressure and temperature of the refrigerant were measured with pressure probes (Testo, Low/High pressure probes, 0638.01941, Freiburg, Germany) and surface temperature probes (Testo, Temperature probes, 0628.0019, Freiburg, Germany), respectively. All measured values were observed and recorded with a multi-function instrument (Testo 350-XL/454, Control unit, Freiburg, Germany) and loggers.
2.4.
Experimental uncertainty
Although error and uncertainty are related concepts, they should not be mixed up. While error is defined as the difference between an individual measurement result and the real value, uncertainty is a statistical concept based on error sources. Hence, uncertainty analysis is a practical tool to determine the magnitude and relevance of the error sources (Calvet et al., 2013). In the present study, temperature, relative humidity, mass losses and drying times were measured with appropriate instruments (as explained above), and total uncertainties for all these parameters were calculated individually. The accuracy of the temperature measuring equipment was ±0.2 C and the reading errors for the temperature measurements were assumed as ±0.1 C. The accuracy of the digital balance used in determination of the moisture content of the sample was ±0.0005 g and the reading errors were assumed as ±0.0001 g. The accuracy of the velocity probes used in the air velocity measurements was ±0.2 m s1 and the error coming from the flow disorder was assumed as ±0.05 m s1. The accuracy of the relative humidity probes was ±2% RH and the reading errors were assumed as ±0.1% RH. Furthermore, the pressure and
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drying system are listed in Table 1. With respect to the results of advanced exergy analysis, four useful terms, which are called unavoidable-endogenous (UNEN), unavoidableexogenous (UNEX), avoidable-endogenous (AVEN) and avoidable-exogenous (AVEX) exergy destruction rates, and modified exergy efficiencies can be calculated (Erbay & Hepbasli, 2013; Kelly, 2008; Kelly et al., 2009; Morosuk, Tsatsaronis, & Zhang, 2012; Petrakopoulou, Tsatsaronis, Morosuk, & Carassai, 2012; Tsatsaronis & Morosuk, 2008, 2009, 2010). The modified exergy efficiency term is one of the most important performance parameters as it is focused on the avoidable endogenous exergy destructions that indicate the realistic improvement potential of the component by focussing on the component itself (Tsatsaronis & Morosuk, 2008): 3 modified
¼
E_ p;k UN AVEX E_ f ;k E_ d;k E_ d;k
100
(3)
3.2. Conventional exergoeconomic analysis of the drying system
Fig. 2 e Flow diagram for advanced exergy analysis method.
In a conventional economic analysis, a cost balance is formulated for the process at steady-state conditions: temperature of the refrigerant were measured with accuracy of ±1.0% and ±0.1 C, respectively. While the accuracy of the electricity meter was ±0.2 A and the reading error was assumed as ±0.1 A for electric current measurements, they were ±5 and ±1 V respectively for electric potential difference measurements. According to all these uncertainties and errors, a detailed uncertainty analysis was performed using the method described by Holman (2001, pp. 48e143) for the experimental measurements of the thermal parameters and the total uncertainties of the predicted values: " UF ¼
3.
vF u1 vx1
2 þ
vF u2 vx2
2 þ/þ
vF un vxn
2 #1=2 (1)
X
C_ k þ Z_ T ¼
X
C_ k þ C_ work þ C_ heat
(4)
out
in
Due to the exergoeconomic aspects, the cost balance is written as (Lazzaretto & Tsatsaronis, 2006; Tsatsaronis & Morosuk, 2008, 2009): C_ p ¼ C_ f þ Z_ T
(5)
C_ k ¼ ck E_ k
(6)
Z_ T ¼ Z_ CI þ Z_ OM
(7)
Before calculating the hourly levelised capital investment cost and operating and maintenance cost of the drying system, a capital recovery factor (CRF) is calculated (Kotas, 1995)
Analyses
n
3.1. Conventional and advanced exergy analyses of the drying system Conventional and advanced exergy analyses were performed according to the equations and method described by Erbay and Hepbasli (2013). Exergy efficiency is defined as the ratio of total exergy out to total exergy in where “out” refers to “net output” or “product” or “desired value”, and “in” refers to “given” or “used” or “fuel”. 3
¼
E_ p 100 E_ f
(2)
In an advanced exergy analysis, exergy destruction of each drying system component is split into endogenous and exogenous and/or avoidable and unavoidable parts (Tsatsaronis & Morosuk, 2010). The methodology used to perform advanced exergy analysis for the HP drying system considered in this study is summarised in a flow diagram shown in Fig. 2 (Erbay & Hepbasli, 2013, 2014) while the most favourable (unavoidable) and theoretical operating conditions assumed for the HP
CRF ¼
iði þ 1Þ n ði þ 1Þ 1
(8)
CRF Z_ CI ¼ PEC top _ZOM ¼ Z_ CI 4
(9) (10)
Table 1 e Assumptions made for performing advanced exergy analysis under the theoretical and unavoidable conditions. Item no
Component
I II
Compressor Condenser
IV
Evaporator
V VI VII
Drying duct Drying cabinet HRU
Theoretical conditions
Unavoidable conditions
his ¼ 100% DT ¼ 10 C DP ¼ 0 DT ¼ 0 C DP ¼ 0 DT ¼ 0 C DT ¼ 1 C DT ¼ 0 C DP ¼ 0
his ¼ 94% DT ¼ 15 C DP ¼ 1% DT ¼ 5 C DP ¼ 1% DT ¼ 0:5 C DT ¼ 2 C DT ¼ 5 C DP ¼ 1%
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Table 2 e Exergy and exergoeconomy balance equations for components of the drying system. #
Control volume
Exergy/exergoeconomy balance equations
I
E_ w ðE_ 2r E_ 1r Þ ¼ E_ d;comp C_ w þ Z_ T;comp ¼ ðC_ 2r C_ 1r Þ
II
ðE_ 2r E_ 3r Þ ðE_ 1a E_ 7a Þ ¼ E_ d;cond ðC_ 2r C_ 3r Þ þ Z_ T;cond ¼ ðC_ 1a C_ 7a Þ c2r ¼ c3r ðFruleÞ
III
E_ 3r E_ 4r ¼ E_ d;exp C_ 3r þ Z_ T;exp ¼ C_ 4r
IV
ðE_ 5a E_ 6a Þ ðE_ 1r E_ 4r Þ ¼ E_ d;evap C_ 5a þ C_ 4r þ Z_ T;evap ¼ C_ 6a þ C_ 1r c5a ¼ c6a ðFruleÞ
V
E_ 1a E_ 2a ¼ E_ d;dd1 E_ 3a E_ 4a ¼ E_ d;dd2 C_ 1a þ Z_ T;dd1 ¼ C_ 2a C_ 3a þ Z_ T;dd2 ¼ C_ 4a
VI
ðE_ 2a E_ 3a Þ þ ðE_ 1p E_ 2p Þ E_ ev ¼ E_ d;dc ðC_ 2a C_ 3a Þ þ ðC_ 1p C_ 2p Þ þ Z_ T;dc ¼ C_ ev c2a ¼ c3a ; c1p ¼ c2p ðFruleÞ
VII
ðE_ 4a E_ 5a Þ ðE_ 7a E_ 6a Þ ¼ E_ d;HRU ðC_ 4a C_ 5a Þ þ Z_ T;HRU ¼ ðC_ 7a C_ 6a Þ c4a ¼ c5a ðFruleÞ
where i, n, top, PEC and 4 are the interest rate on capital, the period of payment, the time of operation of the plant per year, the purchased equipment cost, and the factor of the operating and maintenance costs. These values were taken to be 0.1, 5 year, 3745 h year1, 18875 $ and 0.85, respectively, for the HP drying system used in this study. The cost rate for the component of the drying system is obtained from CRk ¼
PECk PECOS
(11)
In addition to the exergy balance equations, the cost balance and auxiliary equations for the components of the HP drying system are given in Table 2. Tsatsaronis and Morosuk (2009) mentioned that the real cost sources in an energy conversion system were (a) capital investment for the system, (b) operating and maintenance expenses, (c) cost of exergy destruction within each component, and (d) cost of exergy losses from the overall system. The last two terms can be revealed only through an
exergoeconomic analysis. The cost rate associated with the destructions indicates how much (in $ h1) is destroyed during the process and is defined as: C_ d ¼ cf E_ d
(12)
Finally, the total cost is calculated as; C_ T ¼ C_ d þ Z_ T
(13)
Furthermore, the relative significance of non-exergy related costs (capital investment costs, and operating and maintenance expenses) and exergy related costs (costs of destructions and losses) should be known to evaluate the system performance and this can be interpreted by the exergeconomic factor (Tsatsaronis & Morosuk, 2008, 2009) f¼
Z_ T C_ T
(14)
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3.3. Advanced exergoeconomic analysis of the drying system In the conventional exergoeconomic analysis, a cost value is assigned to each exergy stream. In the advanced exergoeconomic analysis, the cost rate associated with the exergy destructions consists of an unavoidable part and an avoidable part, and the following equation is derived from Equation (12) (Cziesla, Tsatsaronis, & Gao, 2006): UN UN AV AV C_ d;k ¼ cf ;k E_ d;k ¼ cf ;k E_ d;k þ E_ d;k ¼ C_ d;k þ C_ d;k
(15)
The avoidable cost rate of exergy destruction is the cost of the fuel used to cover the avoidable exergy destruction in the component when the overall exergetic product fixed as constant. Similarly, endogenous and exogenous cost rates associated with the exergy destructions can be calculated from (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): EN EN C_ d;k ¼ cf ;k E_ d;k
(16)
EX EX C_ d;k ¼ cf ;k E_ d;k
(17)
Because of the technical limitations imposed, the unavoidable investment costs per unit of product exergy ðZ_ T;k =E_ p;k ÞUN can be obtained by taking account of an extremely inefficient type of the kth component, which would never be realised in practice on the ground of the excessive fuel costs associated with it. In practical applications, the term ðZ_ T;k =E_ p;k ÞUN is determined by arbitrarily selecting a set of thermodynamic parameters for this component that lead to a very inefficient solution and by estimating the investment costs for this solution (Cziesla et al., 2006; Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): UN REAL Z_ T;k ¼ E_ p;k
Z_ T;k _ Ep;k
!UN (18)
UN PECUN REAL k ¼ Z_ T;k Z_ T;k PECREAL k
(19)
UN AV Z_ T;k ¼ Z_ T;k þ Z_ T;k
(20)
The endogenous part is associated only with the costs occurring within the kth component when all other components operate theoretically and the component being considered operates with its real case. Under these conditions, the system overall exergetic product was kept constant and the thermodynamic parameters were calculated. Endogenous and exogenous parts of investment costs can be determined using this concept as follows (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): EN EN Z_ T;k ¼ E_ p;k
Z_ T;k E_ p;k
EN EX Z_ T;k ¼ Z_ T;k þ Z_ T;k
!REAL
AVEN and AVEX exergy destructions) can be calculated. The costs, which arose from the system component itself and could be eliminated, can be determined by calculating the avoidable-endogenous exergy destruction costs and investment costs. Furthermore, the costs that can be reduced by structural improvements of the overall system, or by improving the efficiencies of the remaining components, and by improving the efficiency of the component being considered can be revealed by calculating avoidable-exogenous exergy destruction costs and investment costs. These terms are obtained from the equations shown below (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): AVEN AVEN C_ d;k ¼ cf ;k E_ d;k
(23)
AVEX AVEX C_ d;k ¼ cf ;k E_ d;k
(24)
UNEN UNEN C_ d;k ¼ cf ;k E_ d;k
(25)
UNEX UNEX C_ d;k ¼ cf ;k E_ d;k
(26)
UNEN EN Z_ T;k ¼ E_ p;k
Z_ T;k E_ p;k
!UN (27)
UN UNEN UNEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(28)
AV AVEN AVEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(29)
EN UNEN AVEN Z_ T;k ¼ Z_ T;k þ Z_ T;k
(30)
EX UNEX AVEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(31)
Furthermore, the exergoeconomic factor and the total cost in the conventional exergoeconomic analysis can be modified to characterise the process or component more clearly by the help of the calculated advanced exergoeconomic parameters. In the advanced exergoeconomic evaluation, the modified AVEN exergeoconomic factor (f AVEN ) and the total cost (C_ T;k ) are exclusively calculated based on the AVEN cost rates as follows: fkAVEN ¼
AVEN Z_ T;k AVEN Z_ T;k
AVEN þ C_ d;k
100
AVEN AVEN AVEN C_ T;k ¼ Z_ T;k þ C_ d;k
3.4.
(32)
(33)
Assumptions made
The following assumptions were made in the analyses: (21)
(22)
By combining the two splitting concepts (AV/UN and EN/ EX) that were calculated for the exergetic destructions in the advanced exergy analysis, the four useful terms (UNEN, UNEX,
(a) All processes were steady state and steady flow with negligible potential and kinetic energy effects and no chemical or nuclear reactions. (b) The heat transfer to the system and the work transfer from the system were positive. (c) The compressor mechanical hcomp,mech and the compressor motor electrical hcomp,elec efficiencies
35
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
drying system used in food drying. As the analyses were based on experimental data, the errors and uncertainties were important for the accuracy of the results. Uncertainties associated with the experimental measurements and some predicted values are listed in Table 3. The maximum uncertainty values were less than 5%, which was reasonable for an experimental study (Ramaswamy, Balasubramaniam, & Sastry, 2007; Yamamura, Ohara, Mawatari, & Kage, 2009). The investment and hourly levelised costs calculated for the HP drying system used in this study are shown in Table 4. The highest investment cost was for the drying cabinet, followed by the compressor, the evaporator, the HRU and the condenser. According to the investment costs, the expansion valve and the drying ducts were not important system components (Table 4). The HRU had the highest cost of exergy destructions, followed by the evaporator and the drying cabinet whilst the compressor had clearly the lowest destruction costs in the HP drying system (Table 5). The conventional exergoeconomic analysis showed that the expansion valve and the drying ducts were not significant system components with respect to lowering the costs, whereas the HRU, the drying cabinet and the evaporator were important components.
Table 3 e Uncertainties of the experimental measurements and total uncertainties for predicted values. Parameter
Unit
Experimental measurements Uncertainty in the temperature measurement Uncertainty in the weight measurement Uncertainty in the air velocity measurement Uncertainty in the measurement of relative humidity of air Uncertainty in the pressure measurement Uncertainty in the surface temperature measurement Uncertainty in the electric current measurement Uncertainty in the electric potential difference measurement Predicted values Total uncertainty for Total uncertainty for Total uncertainty for Total uncertainty for Total uncertainty for a b c d e
Comment ±0.224
C
g M s1
±0.00051 ±0.21
%
±0.41
kPa C
±1.0% ±1.0
A
±0.224
V
±5.1
kW kW kW % $ h1
±1.6%a ±1.8%b ±3.9%c ±2.7%d ±1.7%e
Nominal value was taken as 6.863. Nominal value was taken as 2.914. Nominal value was taken as 3.497. Nominal value was taken as 87.1. Nominal value was taken as 13.891.
4.1.
All components of the HP drying system except the expansion valve were considered separately and the effect of the inlet drying air temperature on the thermoeconomic system performance was investigated in advanced exergoeconomic analysis. For some components, such as the expansion valve, it is impossible to achieve ideal operations because of difficulties in defining an ideal process associated with such components (Erbay & Hepbasli, 2013; Kelly, 2008). The exergy efficiency of the expansion valve cannot be held constant, while other components vary, and advanced analysis was not performed for the expansion valve in this study. There are three heat exchangers in the HP dryer. From the exergetic/exergoeconomic analyses, the most important one was the HRU. The effect of the inlet drying temperature on the exergy destruction costs was remarkable for the HRU. The rise in inlet drying temperature caused a significant increase in the exergy destruction costs and the main reason for this variation was the increase in the UNEN exergy destruction costs. The increment of the inlet drying temperature from 45 C to 55 C caused an increase of 3.7 times. However, the
were 72 and 75%, respectively (Erbay, Icier, & Hepbasli, 2010). (d) Air acts as an ideal gas with a constant specific heat. (e) The reference-dead state conditions were determined as T0 ¼ 10 C, P0 ¼ 101.325 kPa and ø0 ¼ 60% for air, and T0 ¼ 10 C, P0 ¼ 101.325 kPa for refrigerant. (f) Cpa was 1.005 kJ kg1 K1, Cpv was 1.872 kJ kg1 K1, Ra was 0.287 kJ kg1 K1 and Rv ¼ 0.4615 kJ kg1 K1 and were assumed as constant in all calculations (Çengel & Boles, 2006). The mass flow rate calculations were made using MATLAB (Version 7.7.0.471, The MathWorks Inc., Massachusetts, USA).
4.
Advanced exergoeconomic analysis
Results and discussion
The conventional and advanced exergoeconomic analyses were performed to determine the cost performance of the HP
Table 4 e Hourly levelised cost rates associated with capital investments for the HP drying system. Item no
Component
PEC ($)
CR ()
Z_ CI ($/h)
Z_ OM ($ h1)
Z_ T ($ h1)
I II III IV V VI VII
Compressor Condenser Expansion valve Evaporator Drying ducts Drying cabinet HRU
3500 2650 680 3090 680 5550 2725
0.19 0.14 0.04 0.16 0.04 0.29 0.14
0.25 0.19 0.05 0.22 0.05 0.39 0.19
0.21 0.16 0.04 0.19 0.04 0.33 0.16
0.46 0.35 0.09 0.40 0.09 0.72 0.36
IeV IeVII
HP OS
9920 18,875
0.53 1.00
0.70 1.33
0.59 1.13
1.29 2.46
36
(1.9%) (5.8%) (1.9%) (11.8%) (15.8%) (15.0%) (48.2%) (56.6%) (54.5%) (38.1%) (37.2%) (34.7%) (40.6%) (39.5%) (36.9%) (46.3%) (52.2%) (56.2%) 0.001 0.005 0.001 0.123 0.170 0.170 1.676 1.879 1.583 0.378 0.410 0.333 0.938 0.918 0.833 2.741 3.391 4.209 (58.7%) (60.3%) (51.6%) (74.4%) (70.2%) (63.3%) (26.6%) (18.3%) (20.0%) (12.8%) (18.6%) (14.3%) (18.0%) (19.7%) (23.7%) (35.7%) (25.1%) (0.6%) 0.038 0.047 0.036 0.773 0.756 0.720 0.926 0.607 0.581 0.127 0.205 0.137 0.413 0.457 0.567 2.112 1.629 0.048 0.005 (7.1%) 0.004 (5.6%) 0.006 (9.1%) 0.043 (4.2%) 0.046 (4.3%) 0.086 (7.6%) 0.100 (2.9%) 0.100 (3.0%) 0.116 (4.0%) 0.019 (1.9%) 0.013 (1.2%) 0.011 (1.1%) 0.017 (0.8%) 0.005 (0.2%) 0.006 (0.2%) 0.361 (6.1%) 0.363 (5.6%) 0.610 (8.2%) (32.3%) (28.3%) (37.5%) (9.6%) (9.7%) (14.2%) (22.3%) (22.1%) (21.4%) (47.2%) (43.0%) (49.8%) (40.4%) (40.5%) (39.1%) (12.0%) (17.2%) (35.0%) 0.021 0.022 0.026 0.100 0.105 0.161 0.777 0.733 0.622 0.468 0.474 0.478 0.926 0.942 0.936 0.710 1.114 2.618 0.040 0.051 0.037 0.896 0.925 0.890 2.602 2.486 2.164 0.505 0.615 0.470 1.351 1.376 1.450 4.852 5.020 4.256 0.026 0.026 0.032 0.143 0.151 0.247 0.877 0.832 0.738 0.487 0.487 0.489 0.944 0.947 0.941 1.071 1.477 3.228 0.006 0.009 0.008 0.166 0.216 0.254 1.776 1.978 1.699 0.397 0.423 0.344 0.956 0.924 0.888 3.101 3.754 4.819 0.060 0.068 0.062 0.873 0.860 0.881 1.704 1.340 1.204 0.595 0.680 0.616 1.339 1.399 1.503 2.822 2.744 2.665 0.066 0.077 0.070 1.039 1.077 1.137 3.479 3.318 2.902 0.992 1.102 0.959 2.294 2.323 2.391 5.923 6.497 7.484 Condenser
Evaporator
Drying ducts
Drying cabinet
HRU
II
IV
V
VI
VII
45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 Compressor I
AVEX C_ d;k AVEN C_ d;k UNEX C_ d;k UNEN C_ d;k
UN C_ d;k ($ h1) AV C_ d;k ($ h1) UN C_ d;k ($ h1) EX C_ d;k ($ h1) EN C_ d;k ($ h1)
C_ d;k ($ h1) Drying temperature ( C) Component #
Table 5 e Results of the cost rate associated with exergy destructions for the HP drying system at different drying air temperatures.
AV C_ d;k ($ h1)
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
biggest proportion of the exergy destruction costs was AV. While the proportion of the AV destruction cost to the total destruction cost at 45 C was 82.0%, it decreased to 56.8% at 55 C (Table 5). The major type of investment costs in the HRU was detected as EN with the proportion ranging from 74.7% to 91.2%. Additionally, the AV destruction costs were calculated as between 46.2% and 52.8% of the overall destruction costs (Table 6). While the exergy destruction costs that were accumulated in another heat exchanger used as the evaporator in the system decreased with increasing drying temperature, 75% of the total exergy destruction costs were AV (Table 5). The EN, UN and UNEN investment costs were a considerable proportion of the overall investment costs with values between 84.3% and 88.6%, 59.0% and 62.4% and 52.6% and 53.8%, respectively (Table 6). The third heat exchanger (condenser) was used to transfer energy from the refrigerant to the drying air. While a substantial proportion of the destruction costs of the condenser were EN (approximately 80%) and AV (approximately 85%), two-thirds and half of the overall investment costs were EN and AV, respectively (Tables 5 and 6). Of the destruction costs that occurred in the drying cabinet, 60% were EN or AV. The UNEX destruction costs were extremely low (less than 1% of the overall value), whereas the AVEX destruction costs were remarkably high being in the range of 36.9%e40.6% of the total destruction costs (Table 5). In addition, almost all the investment costs were EN (Table 6). Briefly, the investment costs would be decreased by structural improvements of the component, whereas the destruction costs would be reduced via optimisation of the drying process. Consequently, optimisation studies focused on the drying process are very important due to the energy and cost efficiency (Erbay & Hepbasli, 2013). The exergy destruction costs in the compressor were a small proportion of the total destruction costs (under 1%) (Table 5). Therefore, improvements concentrated on the destructions occurring in the compressor would have limited importance and the investment costs, which were approximately 85% of the overall costs, should be in the foreground of the improvement actions. However, 30% of the overall investment costs were AV and only 24.6%e25.7% were AVEN (Table 6). Consequently, the actions that would focus on the compressor should be about the structural improvements of the component to reduce investment costs. Although there was some importance of the costs occurred in the drying ducts, 34.7%e38.1% of the overall destruction costs were AVEX (Table 5). On the other hand, the majority of total investment costs were EN, whereas 58.4%e60.0% of them were AVEN (Table 6). In other words, optimisation of the system performance is important to lower the destruction costs by reducing the inefficiencies resulting from the component interactions, while the internal structural improvements are essential to reduce the investment costs.
4.2. Comparison of conventional and advanced exergoeconomic analyses Although the irreversibilities/costs accumulated in the system components can be determined by the conventional exergetic/exergoeconomic analysis, their sources and real
37
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Table 6 e Results of the hourly levelised cost of investments for the HP drying system at different drying air temperatures. #
Component
I
Compressor
II
Condenser
IV
Evaporator
V
Drying ducts
VI
Drying cabinet
VII HRU
EN EX UN AV Drying Z_ T;k ($ h1) Z_ T;k ($ h1) Z_ T;k Z_ T;k 1 temperature ( C) ($ h ) ($ h1)
45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 45 50 55
0.374 0.381 0.367 0.241 0.239 0.225 0.357 0.354 0.340 0.085 0.086 0.087 0.723 0.723 0.723 0.265 0.303 0.324
0.082 0.075 0.089 0.105 0.106 0.121 0.046 0.048 0.063 0.003 0.002 0.002 0.000 0.000 0.000 0.090 0.052 0.032
improvement potentials cannot be exactly established. Using advanced techniques, the effects of the component interactions and technological limitations on the efficiency of the system as well as the real potential for improvements can be estimated (Petrakopoulou et al., 2012). The main performance parameters calculated in this study using the conventional and advanced exergetic/exergoeconomic analyses, such as the exergy efficiency, the total costs and the exergoeconomic factor, are listed in Table 7. There was an increase in the total costs of the HRU with the rise in the drying temperature. However, the AVEN costs dramatically decreased (Table 7). Similar tendencies were detected in the variation of 3 modified and f AVEN . While 3 modified advanced to 99.0%, f AVEN increased to 78.4% at the drying temperature of 55 C (Table 7). Namely, the costs increased and the cost reducing potentials decreased with the rise in the drying temperature. As a consequence, the low temperature drying should be chosen to increase the cost performance of the HRU. While the total costs of the drying cabinet were two-fold higher than those of the condenser, the AVEN total costs of the drying cabinet were lower (Table 7). Likewise, the exergetic efficiencies of the drying cabinet were not so much greater (85.1%e86.5%), although 3 modified values were dramatically high (96.4%e96.9%). The main reason for this was that the losses of the drying process, which were unavoidable, occurred in the drying cabinet. The second lowest 3 modified values were calculated for the condenser (82.4%e84.0%). Moreover, the AVEN total costs of the condenser were higher than that of the evaporator (except for 45 C). These calculated results indicated that the condenser was an important system component with respect to cost reduction. The actions focused on the condenser would cause significant decrease in total costs. Although the total costs accumulated in the condenser were 7% of the overall costs and lower than the total costs of the HRU, the drying cabinet and the evaporator regarding the conventional exergoeconomic analysis, the total costs of the condenser were a considerable proportion of the overall system costs (14.9%e16.0%) by the
0.319 0.322 0.311 0.174 0.176 0.170 0.238 0.246 0.251 0.035 0.034 0.034 0.391 0.391 0.391 0.136 0.136 0.166
0.137 0.135 0.146 0.172 0.170 0.176 0.165 0.156 0.151 0.054 0.055 0.054 0.332 0.332 0.332 0.220 0.220 0.189
AV Z_ T;k ($ h1)
UN Z_ T;k ($ h1) UNEN Z_ T;k
UNEX Z_ T;k
0.262 (57.4%) 0.268 (58.8%) 0.250 (54.8%) 0.121 (35.0%) 0.122 (35.0%) 0.111 (32.0%) 0.211 (52.3%) 0.217 (53.8%) 0.212 (52.6%) 0.033 (37.7%) 0.033 (37.3%) 0.034 (38.0%) 0.391 (54.1%) 0.391 (54.1%) 0.391 (54.1%) 0.101 (28.5%) 0.116 (32.6%) 0.151 (42.5%)
0.058 (12.6%) 0.053 (11.7%) 0.061 (13.3%) 0.053 (15.2%) 0.054 (15.6%) 0.059 (17.2%) 0.027 (6.7%) 0.030 (7.3%) 0.039 (9.8%) 0.001 (1.5%) 0.001 (1.0%) 0.001 (0.8%) 0.000 (0.0%) 0.000 (0.0%) 0.000 (0.0%) 0.034 (9.7%) 0.020 (5.6%) 0.015 (4.2%)
AVEN Z_ T;k
0.112 0.112 0.117 0.120 0.117 0.114 0.146 0.138 0.128 0.052 0.053 0.053 0.332 0.332 0.332 0.164 0.188 0.172
(24.6%) (24.6%) (25.7%) (34.7%) (34.0%) (33.1%) (36.3%) (34.2%) (31.7%) (58.4%) (60.0%) (59.9%) (45.9%) (45.9%) (45.9%) (46.2%) (52.8%) (48.6%)
AVEX Z_ T;k
0.025 0.022 0.028 0.052 0.052 0.061 0.019 0.019 0.024 0.002 0.001 0.001 0.000 0.000 0.000 0.056 0.032 0.017
(5.4%) (4.9%) (6.2%) (15.1%) (15.1%) (17.7%) (4.7%) (4.7%) (5.9%) (2.3%) (1.6%) (1.3%) (0.0%) (0.0%) (0.0%) (15.6%) (9.0%) (4.7%)
advanced exergoeconomic analysis. Namely, advanced exergoeconomic analysis showed that the condenser was the second most important system component (after the HRU) with regard to the potential to reduce total costs of the overall system. Similarly, the total costs occurred in the drying ducts were 5.4%e6.4% of the overall system due to the conventional analysis, whereas the AVEN total costs varied in the range of 3.2% and 4.6%. As a consequence, there are strict limits to the scope to improve the system performance and to reduce the costs due to the recent technological development as 3 modified values were calculated in the range of 99.3% and 99.6% (Table 7).
5.
Conclusions
We have applied the conventional and advanced exergoeconomic analyses to a pilot scale HP food dryer for different drying air temperatures in this study. We have separately analysed the components of the drying system and investigated the effects of the operating temperature on the system components. We may list the main conclusions we drawn from the results of the present study as follows: 1. The most important system component was the HRU regarding the cost accumulation. 2. The experimental results suggested that increase in the inlet drying temperature caused lower costs and higher improvement potentials. 3. Concerning the concept for increasing the efficiencies and decreasing the costs, the condenser was the fourth important system component in the conventional exergy analysis, while the second important component in the advanced exergoeconomic analysis. On the contrary, so few interventions that would cause valuable improvements in the costs can be done to the drying ducts due to the advanced exergoeconomic analysis. 4. It may be concluded that the realistic potential improvements and the priorities, which cannot be obtained from conventional exergy-based analyses only, can be
38
76.6 13.7 18.0 27.9 37.0 78.4 70.7 13.5 18.5 20.6 42.1 10.3 74.5 13.4 13.6 28.9 44.6 7.2 0.15 0.83 0.71 0.19 0.90 0.22 94.4 84.0 94.7 99.6 96.4 99.0 91.8 83.3 94.4 99.3 96.8 72.2 92.9 82.4 91.4 99.5 96.9 65.9
0.15 0.89 1.07 0.18 0.74 2.28
0.16 0.87 0.74 0.26 0.79 1.82
50 C 45 C 55 C 50 C 45 C 55 C 50 C
86.8 23.3 12.2 8.5 23.2 4.5 85.5 24.3 10.8 7.4 23.8 5.2 87.4 25.0 10.4 8.2 24.0 5.7 0.53 1.48 3.31 1.05 3.11 7.84 0.53 1.42 3.72 1.19 3.05 6.85 0.52 1.38 3.88 1.08 3.02 6.28 89.6 76.9 78.0 97.1 86.5 37.6 87.1 77.8 75.4 96.4 85.8 39.5 Compressor Condenser Evaporator Drying ducts Drying cabinet HRU I II IV V VI VII
88.5 77.7 73.9 96.5 85.1 40.8
Component
45 C
50 C
55 C
45 C
50 C
55 C
45 C
50 C
55 C
45 C
AVEN C_ T ($ h1)
(%) 3 modified
f (%) C_ T ($ h1)
Conventional methods
(%) 3
determined to decide about the system components to be modified through the advanced-exergy based approaches. Therefore, the method used in this study may be a useful example to analyse the industrial scale drying systems. 5. Optimisation studies focussing on drying foods in terms of energy and/or cost efficiencies and product quality should be done.
Acknowledgements The authors are grateful for the financial support provided for the project entitled “Design, test and performance evaluation of a gas engine-driven solar assisted band conveyor heat pump drying system” under project no: 106M482 by The Scientific and Technological Research Council of Turkey (TUBITAK). They also thank the reviewers for their valuable comments as well as the Editor for his additional useful comments, which have been used in improving the quality of the article.
references
Item no
Table 7 e Comparison of the results of exergetic and exergoeconomic analyses for conventional and advanced methods.
Advanced methods
f AVEN (%)
55 C
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
AOAC. (1990). In K. Heldrich (Ed.), Official methods of analysis of the association of official analytical chemists (15th ed.). Arlington, Virginia, USA: AOAC. Calvet, S., Gates, R. S., Zhang, G., Estelles, F., Ogink, N. W. M., Pedersen, S., et al. (2013). Measuring gas emissions from livestock buildings: a review on uncertainty analysis and error sources. Biosystems Engineering, 116, 221e231. Çengel, Y. A., & Boles, M. A. (2006). Thermodynamics an engineering approach (5th ed.). NJ, USA: McGraw-Hill. Cziesla, F., Tsatsaronis, G., & Gao, Z. (2006). Avoidable thermodynamic inefficiencies and costs in an externally fired combined cycle power plant. Energy, 31, 1472e1489. Erbay, Z., & Hepbasli, A. (2013). Advanced exergy analysis of a heat pump drying system used in food drying. Drying Technology, 31(7), 802e810. Erbay, Z., & Hepbasli, A. (2014). Application of conventional and advanced exergy analyses to evaluate the performance of a ground-source heat pump (GSHP) dryer used in food drying. Energy Conversion and Management, 78, 499e507. Erbay, Z., & Icier, F. (2010). A review of thin layer drying of foods: theory, modeling and experimental results. Critical Reviews in Food Science and Nutrition, 50(5), 441e464. Erbay, Z., Icier, F., & Hepbasli, A. (2010). Exergetic performance assessment of a pilot-scale heat pump belt conveyor dryer. International Journal of Energy Research, 34(3), 249e264. Hepbasli, A. (2012). Low exergy (LowEx) heating and cooling systems for sustainable buildings and societies. Renewable and Sustainable Energy Reviews, 16(1), 73e104. Hepbasli, A., Erbay, Z., Colak, N., Hancioglu, E., & Icier, F. (2010). Exergetic performance assessment of three different food driers. Proceedings of Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 224(1), 1e12. Holman, J. P. (2001). Experimental methods for engineers (7th ed.). Singapore: McGraw Hill. Jangam, S. V. (2011). An overview of recent developments and some R&D challenges related to drying of foods. Drying Technology, 29(12), 1343e1357. Kelly, S. (2008). Energy systems improvement based on endogenous and exogenous exergy destruction. PhD Thesis. Berlin, Germany: € t Berlin. Institut fu¨r Energietechnik, Technische Universta
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Kelly, S., Tsatsaronis, G., & Morosuk, T. (2009). Advanced exergetic analysis: approaches for splitting the exergy destruction into endogenous and exogenous parts. Energy, 34, 384e391. Keçebas‚, A., & Hepbasli, A. (2014). Conventional and advanced exergoeconomic analyses of geothermal district heating systems. Energy and Buildings, 69, 434e441. Kotas, T. J. (1995). The exergy method of thermal power plant analysis. Malabar, Florida: Krieger Publishing Company. Kudra, T. (2004). Energy aspects in drying. Drying Technology, 22(5), 917e932. Lazzaretto, A., & Tsatsaronis, G. (2006). SPECO: a systematic and general methodology for calculating efficiencies and costs in thermal systems. Energy, 31, 1257e1289. Minea, V. (2013). Heat-pump-assisted drying: recent technological advances and R&D needs. Drying Technology, 31(10), 1177e1189. Morosuk, T., & Tsatsaronis, G. (2008). A new approach to the exergy analysis of absorbtion refrigeration machines. Energy, 33, 890e907. Morosuk, T., & Tsatsaronis, G. (2009). Advanced exergetic evaluation of refrigeration machines using different working fluids. Energy, 34, 2248e2258. Morosuk, T., Tsatsaronis, G., Boyano, A., & Gantiva, C. (2012). Advanced exergy-based analyses applied to a system including LNG regasification and electricity generation. International Journal of Energy and Environmental Engineering, 3, 1. Morosuk, T., Tsatsaronis, G., & Zhang, C. (2012). Conventional thermodynamic and advanced exergetic analysis of a refrigeration machine using a Voorhees' compression process. Energy Conversion and Management, 60, 143e151. Mujumdar, A. S. (2006). Handbook of industrial drying (3rd ed.). Boca Raton, FL: CRC Press. Petrakopoulou, F., Tsatsaronis, G., Morosuk, T., & Carassai, A. (2012). Conventional and advanced exergetic analyses applied to a combined cycle power plant. Energy, 146e152. Ramaswamy, R., Balasubramaniam, V. M., & Sastry, S. K. (2007). Thermal conductivity of selected liquid foods at elevated pressures up to 700 MPa. Journal of Food Engineering, 83(3), 444e451. Sahoo, P. K. (2008). Exergoeconomic analysis and optimization of a cogeneration system using evolutionary programming. Applied Thermal Engineering, 28, 1580e1588.
39
Shi, Q. L., Xue, C. H., Zhao, Y., Li, Z. J., Wang, X. Y., & Luan, D. L. (2008). Optimization of processing parameters of horse mackerel (Trachurus japonicus) dried in a heat pump dehumidifier using response surface methodology. Journal of Food Engineering, 87, 74e81. € ylemez, M. S. (2006). Optimum heat pump in drying systems So with waste heat recovery. Journal of Food Engineering, 74(3), 292e298. Tarhan, S. (2007). Selection of chemical and thermal pretreatment combination for plum drying at low and moderate drying air temperatures. Journal of Food Engineering, 79, 255e260. Tong, Y., Kozai, T., Nishioka, N., & Ohyama, K. (2010). Greenhouse heating using heat pumps with a high coefficient of performance (COP). Biosystems Engineering, 106, 405e411. Tsatsaronis, G., & Morosuk, T. (2008). A general exergy-based method for combining a cost analysis with an environmental impact analysis, Part I e theoretical Development. In Proceedings of IMECE2008, 2008 ASME International Mechanical Engineering Congress and Exposition, Boston, Massachusetts, USA (pp. 453e462). Tsatsaronis, G., & Morosuk, T. (2009). Understanding and improving energy conversion processes with the aid of exergy-based methods. In 1st International Exergy, Life Cycle Assessment, and Sustainability Workshop and Symposium (ELCAS), Nisyros, Greece. Tsatsaronis, G., & Morosuk, T. (2010). Advanced exergetic analysis of a novel system for generating electricity and vaporizing liquefied natural gas. Energy, 35, 820e829. Vadivambal, R., & Jayas, D. S. (2007). Changes in quality of microwave-treated agricultural products: a review. Biosystems Engineering, 98, 1e16. Yamamura, M., Ohara, K., Mawatari, Y., & Kage, H. (2009). Measuring the drying rate of liquid film coatings using heat flux method. Drying Technology, 27(6), 817e820. Zielinska, M., Zapotoczny, P., Alves-Filho, O., Eikevik, T. M., & Blaszczak, W. (2013). A multi-stage combined heat pump and microwave vacuum drying of green peas. Journal of Food Engineering, 115(3), 347e356.
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.elsevier.com/locate/issn/15375110
Advanced exergoeconomic evaluation of a heat pump food dryer Zafer Erbay a,*, Arif Hepbasli b a
Department of Food Engineering, Faculty of Engineering and Natural Sciences, Adana Science and Technology University, 01180 Seyhan, Adana, Turkey b Department of Energy Systems Engineering, Faculty of Engineering, Yas‚ar University, 35100 Bornova, Izmir, Turkey
article info
In this study, the results of conventional and advanced exergoeconomic analyses of the
Article history:
performance of a pilot scale air-source heat pump food dryer were compared for the first
Received 19 March 2014
time. The contributions of the components of the drying system to the exergetic cost
Received in revised form
effectiveness of the dryer were evaluated, and the effects of changing the inlet drying
3 June 2014
temperature were determined. The most important system component was determined to
Accepted 4 June 2014
be the heat recovery unit, followed by the condenser with respect to the reducing poten-
Published online
tials for the total costs of the overall system. Decreasing temperature caused an increase in the cost performance of drying. The modification of the system components for improving
Keywords:
the efficiency of the system can be effectively determined through advanced exer-
Drying
goeconomic approach by stating the realistic potential improvements and the priorities in
Heat pump
the system. © 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
Exergy Exergoeconomics Advanced exergy Advanced exergoeconomy
1.
Introduction
Drying is a notoriously energy-intensive process and its energy consumption value is 10e25% of the total energy consumption in all industries in developed countries, especially for agricultural and food processing sectors that need the high quality requirement of the dried product, often with relatively low thermal efficiency ranging from 25% to 50% (Kudra, 2004; Mujumdar, 2006; Vadivambal & Jayas, 2007). In the context of rising energy prices and growing concerns about climate change and environmental issues, reducing energy consumption and costs in dryers has become a challenging issue (Erbay & Icier, 2010; Minea, 2013).
Heat pumps (HPs) are known to be energy-efficient devices in drying operations because of their heat recovery potential and relatively high energy utilisation efficiencies (Tong, Kozai, Nishioka, & Ohyama, 2010). In HP drying systems, the sensible and latent heat of the evaporated moisture in the drier can be recovered and recycled back to the drier by reheating the dehumidified air (Jangam, 2011). During the past few decades, HP drying systems and their food applications have been very popular due to their low operating cost (Shi et al., 2008; € ylemez, 2006; Zielinska, Zapotoczny, Alves-Filho, Eikevik, So & Blaszczak, 2013). Exergy can be defined in various ways, as presented comprehensively elsewhere (Hepbasli, 2012). According to one commonly used definition, it is the maximum amount of work
* Corresponding author. Tel.: þ90 322 455 0000x2080; fax: þ90 322 455 0009. E-mail addresses: [email protected] (Z. Erbay), [email protected] (A. Hepbasli). http://dx.doi.org/10.1016/j.biosystemseng.2014.06.008 1537-5110/© 2014 IAgrE. Published by Elsevier Ltd. All rights reserved.
30
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Nomenclature c C_ Cp CR CRF E_ F i n P PEC R T top x u U Z_
1
unit exergy cost ($ GJ ) exergy cost rate ($ h1) specific heat (kJ kg1 C1) cost rate () capital recovery factor () exergy rate (kW) function of the independent variables interest rate on capital period of payment (year) pressure (kPa) purchase equipment cost ($) gas constant (kJ kg1 K1) temperature (K or C) time of operation of plant per year (h) independent variable uncertainty in the independent variables uncertainty in the result hourly levelised cost of investment ($ h1)
Greek letters h energy efficiency (%) 3 exergy (second law) efficiency (%) 4 factor of the operating and maintenance cost Superscripts AV avoidable AVEN avoidable-endogenous AVEX avoidable-exogenous EN endogenous EX exogenous REAL experimental operation conditions
that can be produced by a stream of matter, heat or work as it comes to equilibrium with a reference environment. It is also considered as an important and effective tool for analysing, optimising and improving the energy efficiency of the drying systems. With the help of exergy analysis, magnitudes and locations of irreversibilities (exergy destructions) in the system components considered can be successfully specified. However, this information is not enough to create solution-oriented approaches. A relatively new method, the so-called advanced exergy analysis, should be used to reveal the realistic potential and to predict the activities for the system improvements. Exergy destructions of each drying system component are split into their endogenous and exogenous and/or avoidable and unavoidable parts in this method. In addition, splitting the exergy destructions enables the exergy destruction values from a conventional exergy analysis to be understood (Kelly, 2008). Exergoeconomics (thermoeconomics) is the unique combination of exergy analysis with economic constraints to provide the information that cannot be obtained by conventional energy analysis and economic evaluation. The results of exergoeconomic analysis present cost-effective ways for improving the performance of a system (Sahoo, 2008; Morosuk, Tsatsaronis, Boyano, & Gantiva, 2012). Recently, researchers have started to apply the exergoeconomic analysis with advanced exergy methods to the thermal systems and
UN UNEN UNEX
unavoidable unavoidable-endogenous unavoidable-exogenous
Subscripts a air CI capital investment comp compressor cond condenser d destruction dc drying cabinet dd drying ducts elec electrical exp expansion valve ev evaporation evap evaporator f fuel is isentropic k kth component mech mechanical OM operating and maintenance OS overall system p product r refrigerant T total v vapour w work 0 dead state Abbreviations HP heat pump HRU heat recovery unit
obtained invaluable results (Morosuk, Tsatsaronis, & Zhang, 2012; Tsatsaronis & Morosuk, 2009). There have been a few studies conducted on the application of advanced exergy analysis to refrigeration/HP systems (Erbay & Hepbasli, 2013, 2014; Kelly, Tsatsaronis, & Morosuk, 2009; Morosuk & Tsatsaronis, 2008, 2009; Morosuk, Tsatsaronis, & Zhang, 2012), whereas no studies focused on the advanced exergoeconomic analysis of air-source HP drying systems canbe found in the scientific literature, to the best of the authors' knowledge. This provided the prime motivation behind this contribution, which has the objectives to: (i) perform advanced exergoeconomic analysis of a pilot scale HP drying system used in food drying, (ii) evaluate the exergetic cost effectiveness of the drying system in parts, (iii) investigate the effects of the variation of drying temperature on the exergoeconomic performance, and (iv) discuss the performance and improvement potentials of the drying system.
2.
Materials and methods
2.1.
Plums
Freshly harvested plums (Prunus domestica Insititia) were purchased from a local market in the city of Izmir, Turkey. The
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
1a
R407C was used as refrigerant in the HP system. The drying compartment dimensions were 3.0 1.0 1.0 m. The plums were moved by a conveyor band system driven by an electric motor.
V-1
II
2a
3r
2.3.
2r
III
VI
I 1r 3a
4r
IV 5a
7a I III V VII
Compressor Expansion Valve Drying Ducts Heat Recovery Unit
V-2
6a
VII
4a II IV VI
Condenser Evaporator Drying Cabinet
Fig. 1 e The schematic illustration of components of the HP drying system and streams with coded points used in equations of conventional exergy analysis.
purchased plums were cleaned and dipped into 1% NaOH solution for 15 s (Tarhan, 2007). They were then washed with water, and the excess water on the surface of plums removed with a filter paper. They were sliced uniformly (average thickness: 4.0 ± 0.5 mm) and processed within 24 h. The composition of the plum samples was determined to calculate the specific heat values. The moisture, protein, fat, crude fibre and ash contents of plum samples were found using the methods of AOAC (1990) and the composition of the plums used in the calculations of the specific heat of the fresh plum slices were 84.5 ± 1.1%, 0.8 ± 0.1%, 0.2 ± 0.1%, 1.5 ± 0.2% and 0.6 ± 0.1%, respectively. The average final moisture content of the dried plum slices was 10.4 ± 1.5% (wet basis).
2.2.
31
Experimental setup
The plums were dried in a pilot scale HP conveyor dryer, which was designed and constructed in the Department of Mechanical Engineering, Faculty of Engineering, Ege University, Izmir, Turkey (Hepbasli, Erbay, Colak, Hancioglu, & Icier, 2010). The drying system consisted of two main parts; (1) HP, and (2) drying chamber (Fig. 1). The air was heated by an HP system including a scroll compressor, a condenser, an expansion valve, an evaporator and a heat recovery unit (HRU). The air temperature was controlled by a control unit.
Drying procedure and measurements
Before starting the drying processes, the system was run for at least 1 h to obtain steady-state conditions. The plum slices were spread out in a thin layer. The drying experiments were carried out in triplicate at drying air temperatures of 45, 50 and 55 C with a drying air velocity of 1.5 m s1 and a relative humidity of 10%. The drying process continued until the moisture content of the plums reached an equilibrium value. Humidity, temperature and velocity were measured in the drying chamber with robust humidity probes (Testo, 0636.2140, Freiburg, Germany), vane/temperature probes (Testo, 0635.9540, Freiburg, Germany), using professional telescopic handle for plug-in vane probes (Testo, 0430.0941, Freiburg, Germany). The measurements of drying air temperature, velocity and relative humidity were recorded every 5 min. An infrared thermometer (Testo 552-T2, Freiburg, Germany) and a surface thermometer (METEX ME-32, Seoul, South Korea) were used to measure the surface temperatures of the product and the drying chamber walls, respectively. A digital balance (Scaltec SBA 61, Goettingen, Germany) was used to measure the weight loss of the sample during the drying experiments. The ambient temperature and relative humidity were also measured and recorded. The pressure and temperature of the refrigerant were measured with pressure probes (Testo, Low/High pressure probes, 0638.01941, Freiburg, Germany) and surface temperature probes (Testo, Temperature probes, 0628.0019, Freiburg, Germany), respectively. All measured values were observed and recorded with a multi-function instrument (Testo 350-XL/454, Control unit, Freiburg, Germany) and loggers.
2.4.
Experimental uncertainty
Although error and uncertainty are related concepts, they should not be mixed up. While error is defined as the difference between an individual measurement result and the real value, uncertainty is a statistical concept based on error sources. Hence, uncertainty analysis is a practical tool to determine the magnitude and relevance of the error sources (Calvet et al., 2013). In the present study, temperature, relative humidity, mass losses and drying times were measured with appropriate instruments (as explained above), and total uncertainties for all these parameters were calculated individually. The accuracy of the temperature measuring equipment was ±0.2 C and the reading errors for the temperature measurements were assumed as ±0.1 C. The accuracy of the digital balance used in determination of the moisture content of the sample was ±0.0005 g and the reading errors were assumed as ±0.0001 g. The accuracy of the velocity probes used in the air velocity measurements was ±0.2 m s1 and the error coming from the flow disorder was assumed as ±0.05 m s1. The accuracy of the relative humidity probes was ±2% RH and the reading errors were assumed as ±0.1% RH. Furthermore, the pressure and
32
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
drying system are listed in Table 1. With respect to the results of advanced exergy analysis, four useful terms, which are called unavoidable-endogenous (UNEN), unavoidableexogenous (UNEX), avoidable-endogenous (AVEN) and avoidable-exogenous (AVEX) exergy destruction rates, and modified exergy efficiencies can be calculated (Erbay & Hepbasli, 2013; Kelly, 2008; Kelly et al., 2009; Morosuk, Tsatsaronis, & Zhang, 2012; Petrakopoulou, Tsatsaronis, Morosuk, & Carassai, 2012; Tsatsaronis & Morosuk, 2008, 2009, 2010). The modified exergy efficiency term is one of the most important performance parameters as it is focused on the avoidable endogenous exergy destructions that indicate the realistic improvement potential of the component by focussing on the component itself (Tsatsaronis & Morosuk, 2008): 3 modified
¼
E_ p;k UN AVEX E_ f ;k E_ d;k E_ d;k
100
(3)
3.2. Conventional exergoeconomic analysis of the drying system
Fig. 2 e Flow diagram for advanced exergy analysis method.
In a conventional economic analysis, a cost balance is formulated for the process at steady-state conditions: temperature of the refrigerant were measured with accuracy of ±1.0% and ±0.1 C, respectively. While the accuracy of the electricity meter was ±0.2 A and the reading error was assumed as ±0.1 A for electric current measurements, they were ±5 and ±1 V respectively for electric potential difference measurements. According to all these uncertainties and errors, a detailed uncertainty analysis was performed using the method described by Holman (2001, pp. 48e143) for the experimental measurements of the thermal parameters and the total uncertainties of the predicted values: " UF ¼
3.
vF u1 vx1
2 þ
vF u2 vx2
2 þ/þ
vF un vxn
2 #1=2 (1)
X
C_ k þ Z_ T ¼
X
C_ k þ C_ work þ C_ heat
(4)
out
in
Due to the exergoeconomic aspects, the cost balance is written as (Lazzaretto & Tsatsaronis, 2006; Tsatsaronis & Morosuk, 2008, 2009): C_ p ¼ C_ f þ Z_ T
(5)
C_ k ¼ ck E_ k
(6)
Z_ T ¼ Z_ CI þ Z_ OM
(7)
Before calculating the hourly levelised capital investment cost and operating and maintenance cost of the drying system, a capital recovery factor (CRF) is calculated (Kotas, 1995)
Analyses
n
3.1. Conventional and advanced exergy analyses of the drying system Conventional and advanced exergy analyses were performed according to the equations and method described by Erbay and Hepbasli (2013). Exergy efficiency is defined as the ratio of total exergy out to total exergy in where “out” refers to “net output” or “product” or “desired value”, and “in” refers to “given” or “used” or “fuel”. 3
¼
E_ p 100 E_ f
(2)
In an advanced exergy analysis, exergy destruction of each drying system component is split into endogenous and exogenous and/or avoidable and unavoidable parts (Tsatsaronis & Morosuk, 2010). The methodology used to perform advanced exergy analysis for the HP drying system considered in this study is summarised in a flow diagram shown in Fig. 2 (Erbay & Hepbasli, 2013, 2014) while the most favourable (unavoidable) and theoretical operating conditions assumed for the HP
CRF ¼
iði þ 1Þ n ði þ 1Þ 1
(8)
CRF Z_ CI ¼ PEC top _ZOM ¼ Z_ CI 4
(9) (10)
Table 1 e Assumptions made for performing advanced exergy analysis under the theoretical and unavoidable conditions. Item no
Component
I II
Compressor Condenser
IV
Evaporator
V VI VII
Drying duct Drying cabinet HRU
Theoretical conditions
Unavoidable conditions
his ¼ 100% DT ¼ 10 C DP ¼ 0 DT ¼ 0 C DP ¼ 0 DT ¼ 0 C DT ¼ 1 C DT ¼ 0 C DP ¼ 0
his ¼ 94% DT ¼ 15 C DP ¼ 1% DT ¼ 5 C DP ¼ 1% DT ¼ 0:5 C DT ¼ 2 C DT ¼ 5 C DP ¼ 1%
33
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Table 2 e Exergy and exergoeconomy balance equations for components of the drying system. #
Control volume
Exergy/exergoeconomy balance equations
I
E_ w ðE_ 2r E_ 1r Þ ¼ E_ d;comp C_ w þ Z_ T;comp ¼ ðC_ 2r C_ 1r Þ
II
ðE_ 2r E_ 3r Þ ðE_ 1a E_ 7a Þ ¼ E_ d;cond ðC_ 2r C_ 3r Þ þ Z_ T;cond ¼ ðC_ 1a C_ 7a Þ c2r ¼ c3r ðFruleÞ
III
E_ 3r E_ 4r ¼ E_ d;exp C_ 3r þ Z_ T;exp ¼ C_ 4r
IV
ðE_ 5a E_ 6a Þ ðE_ 1r E_ 4r Þ ¼ E_ d;evap C_ 5a þ C_ 4r þ Z_ T;evap ¼ C_ 6a þ C_ 1r c5a ¼ c6a ðFruleÞ
V
E_ 1a E_ 2a ¼ E_ d;dd1 E_ 3a E_ 4a ¼ E_ d;dd2 C_ 1a þ Z_ T;dd1 ¼ C_ 2a C_ 3a þ Z_ T;dd2 ¼ C_ 4a
VI
ðE_ 2a E_ 3a Þ þ ðE_ 1p E_ 2p Þ E_ ev ¼ E_ d;dc ðC_ 2a C_ 3a Þ þ ðC_ 1p C_ 2p Þ þ Z_ T;dc ¼ C_ ev c2a ¼ c3a ; c1p ¼ c2p ðFruleÞ
VII
ðE_ 4a E_ 5a Þ ðE_ 7a E_ 6a Þ ¼ E_ d;HRU ðC_ 4a C_ 5a Þ þ Z_ T;HRU ¼ ðC_ 7a C_ 6a Þ c4a ¼ c5a ðFruleÞ
where i, n, top, PEC and 4 are the interest rate on capital, the period of payment, the time of operation of the plant per year, the purchased equipment cost, and the factor of the operating and maintenance costs. These values were taken to be 0.1, 5 year, 3745 h year1, 18875 $ and 0.85, respectively, for the HP drying system used in this study. The cost rate for the component of the drying system is obtained from CRk ¼
PECk PECOS
(11)
In addition to the exergy balance equations, the cost balance and auxiliary equations for the components of the HP drying system are given in Table 2. Tsatsaronis and Morosuk (2009) mentioned that the real cost sources in an energy conversion system were (a) capital investment for the system, (b) operating and maintenance expenses, (c) cost of exergy destruction within each component, and (d) cost of exergy losses from the overall system. The last two terms can be revealed only through an
exergoeconomic analysis. The cost rate associated with the destructions indicates how much (in $ h1) is destroyed during the process and is defined as: C_ d ¼ cf E_ d
(12)
Finally, the total cost is calculated as; C_ T ¼ C_ d þ Z_ T
(13)
Furthermore, the relative significance of non-exergy related costs (capital investment costs, and operating and maintenance expenses) and exergy related costs (costs of destructions and losses) should be known to evaluate the system performance and this can be interpreted by the exergeconomic factor (Tsatsaronis & Morosuk, 2008, 2009) f¼
Z_ T C_ T
(14)
34
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
3.3. Advanced exergoeconomic analysis of the drying system In the conventional exergoeconomic analysis, a cost value is assigned to each exergy stream. In the advanced exergoeconomic analysis, the cost rate associated with the exergy destructions consists of an unavoidable part and an avoidable part, and the following equation is derived from Equation (12) (Cziesla, Tsatsaronis, & Gao, 2006): UN UN AV AV C_ d;k ¼ cf ;k E_ d;k ¼ cf ;k E_ d;k þ E_ d;k ¼ C_ d;k þ C_ d;k
(15)
The avoidable cost rate of exergy destruction is the cost of the fuel used to cover the avoidable exergy destruction in the component when the overall exergetic product fixed as constant. Similarly, endogenous and exogenous cost rates associated with the exergy destructions can be calculated from (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): EN EN C_ d;k ¼ cf ;k E_ d;k
(16)
EX EX C_ d;k ¼ cf ;k E_ d;k
(17)
Because of the technical limitations imposed, the unavoidable investment costs per unit of product exergy ðZ_ T;k =E_ p;k ÞUN can be obtained by taking account of an extremely inefficient type of the kth component, which would never be realised in practice on the ground of the excessive fuel costs associated with it. In practical applications, the term ðZ_ T;k =E_ p;k ÞUN is determined by arbitrarily selecting a set of thermodynamic parameters for this component that lead to a very inefficient solution and by estimating the investment costs for this solution (Cziesla et al., 2006; Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): UN REAL Z_ T;k ¼ E_ p;k
Z_ T;k _ Ep;k
!UN (18)
UN PECUN REAL k ¼ Z_ T;k Z_ T;k PECREAL k
(19)
UN AV Z_ T;k ¼ Z_ T;k þ Z_ T;k
(20)
The endogenous part is associated only with the costs occurring within the kth component when all other components operate theoretically and the component being considered operates with its real case. Under these conditions, the system overall exergetic product was kept constant and the thermodynamic parameters were calculated. Endogenous and exogenous parts of investment costs can be determined using this concept as follows (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): EN EN Z_ T;k ¼ E_ p;k
Z_ T;k E_ p;k
EN EX Z_ T;k ¼ Z_ T;k þ Z_ T;k
!REAL
AVEN and AVEX exergy destructions) can be calculated. The costs, which arose from the system component itself and could be eliminated, can be determined by calculating the avoidable-endogenous exergy destruction costs and investment costs. Furthermore, the costs that can be reduced by structural improvements of the overall system, or by improving the efficiencies of the remaining components, and by improving the efficiency of the component being considered can be revealed by calculating avoidable-exogenous exergy destruction costs and investment costs. These terms are obtained from the equations shown below (Keçebas‚ & Hepbasli, 2014; Tsatsaronis & Morosuk, 2008): AVEN AVEN C_ d;k ¼ cf ;k E_ d;k
(23)
AVEX AVEX C_ d;k ¼ cf ;k E_ d;k
(24)
UNEN UNEN C_ d;k ¼ cf ;k E_ d;k
(25)
UNEX UNEX C_ d;k ¼ cf ;k E_ d;k
(26)
UNEN EN Z_ T;k ¼ E_ p;k
Z_ T;k E_ p;k
!UN (27)
UN UNEN UNEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(28)
AV AVEN AVEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(29)
EN UNEN AVEN Z_ T;k ¼ Z_ T;k þ Z_ T;k
(30)
EX UNEX AVEX Z_ T;k ¼ Z_ T;k þ Z_ T;k
(31)
Furthermore, the exergoeconomic factor and the total cost in the conventional exergoeconomic analysis can be modified to characterise the process or component more clearly by the help of the calculated advanced exergoeconomic parameters. In the advanced exergoeconomic evaluation, the modified AVEN exergeoconomic factor (f AVEN ) and the total cost (C_ T;k ) are exclusively calculated based on the AVEN cost rates as follows: fkAVEN ¼
AVEN Z_ T;k AVEN Z_ T;k
AVEN þ C_ d;k
100
AVEN AVEN AVEN C_ T;k ¼ Z_ T;k þ C_ d;k
3.4.
(32)
(33)
Assumptions made
The following assumptions were made in the analyses: (21)
(22)
By combining the two splitting concepts (AV/UN and EN/ EX) that were calculated for the exergetic destructions in the advanced exergy analysis, the four useful terms (UNEN, UNEX,
(a) All processes were steady state and steady flow with negligible potential and kinetic energy effects and no chemical or nuclear reactions. (b) The heat transfer to the system and the work transfer from the system were positive. (c) The compressor mechanical hcomp,mech and the compressor motor electrical hcomp,elec efficiencies
35
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
drying system used in food drying. As the analyses were based on experimental data, the errors and uncertainties were important for the accuracy of the results. Uncertainties associated with the experimental measurements and some predicted values are listed in Table 3. The maximum uncertainty values were less than 5%, which was reasonable for an experimental study (Ramaswamy, Balasubramaniam, & Sastry, 2007; Yamamura, Ohara, Mawatari, & Kage, 2009). The investment and hourly levelised costs calculated for the HP drying system used in this study are shown in Table 4. The highest investment cost was for the drying cabinet, followed by the compressor, the evaporator, the HRU and the condenser. According to the investment costs, the expansion valve and the drying ducts were not important system components (Table 4). The HRU had the highest cost of exergy destructions, followed by the evaporator and the drying cabinet whilst the compressor had clearly the lowest destruction costs in the HP drying system (Table 5). The conventional exergoeconomic analysis showed that the expansion valve and the drying ducts were not significant system components with respect to lowering the costs, whereas the HRU, the drying cabinet and the evaporator were important components.
Table 3 e Uncertainties of the experimental measurements and total uncertainties for predicted values. Parameter
Unit
Experimental measurements Uncertainty in the temperature measurement Uncertainty in the weight measurement Uncertainty in the air velocity measurement Uncertainty in the measurement of relative humidity of air Uncertainty in the pressure measurement Uncertainty in the surface temperature measurement Uncertainty in the electric current measurement Uncertainty in the electric potential difference measurement Predicted values Total uncertainty for Total uncertainty for Total uncertainty for Total uncertainty for Total uncertainty for a b c d e
Comment ±0.224
C
g M s1
±0.00051 ±0.21
%
±0.41
kPa C
±1.0% ±1.0
A
±0.224
V
±5.1
kW kW kW % $ h1
±1.6%a ±1.8%b ±3.9%c ±2.7%d ±1.7%e
Nominal value was taken as 6.863. Nominal value was taken as 2.914. Nominal value was taken as 3.497. Nominal value was taken as 87.1. Nominal value was taken as 13.891.
4.1.
All components of the HP drying system except the expansion valve were considered separately and the effect of the inlet drying air temperature on the thermoeconomic system performance was investigated in advanced exergoeconomic analysis. For some components, such as the expansion valve, it is impossible to achieve ideal operations because of difficulties in defining an ideal process associated with such components (Erbay & Hepbasli, 2013; Kelly, 2008). The exergy efficiency of the expansion valve cannot be held constant, while other components vary, and advanced analysis was not performed for the expansion valve in this study. There are three heat exchangers in the HP dryer. From the exergetic/exergoeconomic analyses, the most important one was the HRU. The effect of the inlet drying temperature on the exergy destruction costs was remarkable for the HRU. The rise in inlet drying temperature caused a significant increase in the exergy destruction costs and the main reason for this variation was the increase in the UNEN exergy destruction costs. The increment of the inlet drying temperature from 45 C to 55 C caused an increase of 3.7 times. However, the
were 72 and 75%, respectively (Erbay, Icier, & Hepbasli, 2010). (d) Air acts as an ideal gas with a constant specific heat. (e) The reference-dead state conditions were determined as T0 ¼ 10 C, P0 ¼ 101.325 kPa and ø0 ¼ 60% for air, and T0 ¼ 10 C, P0 ¼ 101.325 kPa for refrigerant. (f) Cpa was 1.005 kJ kg1 K1, Cpv was 1.872 kJ kg1 K1, Ra was 0.287 kJ kg1 K1 and Rv ¼ 0.4615 kJ kg1 K1 and were assumed as constant in all calculations (Çengel & Boles, 2006). The mass flow rate calculations were made using MATLAB (Version 7.7.0.471, The MathWorks Inc., Massachusetts, USA).
4.
Advanced exergoeconomic analysis
Results and discussion
The conventional and advanced exergoeconomic analyses were performed to determine the cost performance of the HP
Table 4 e Hourly levelised cost rates associated with capital investments for the HP drying system. Item no
Component
PEC ($)
CR ()
Z_ CI ($/h)
Z_ OM ($ h1)
Z_ T ($ h1)
I II III IV V VI VII
Compressor Condenser Expansion valve Evaporator Drying ducts Drying cabinet HRU
3500 2650 680 3090 680 5550 2725
0.19 0.14 0.04 0.16 0.04 0.29 0.14
0.25 0.19 0.05 0.22 0.05 0.39 0.19
0.21 0.16 0.04 0.19 0.04 0.33 0.16
0.46 0.35 0.09 0.40 0.09 0.72 0.36
IeV IeVII
HP OS
9920 18,875
0.53 1.00
0.70 1.33
0.59 1.13
1.29 2.46
36
(1.9%) (5.8%) (1.9%) (11.8%) (15.8%) (15.0%) (48.2%) (56.6%) (54.5%) (38.1%) (37.2%) (34.7%) (40.6%) (39.5%) (36.9%) (46.3%) (52.2%) (56.2%) 0.001 0.005 0.001 0.123 0.170 0.170 1.676 1.879 1.583 0.378 0.410 0.333 0.938 0.918 0.833 2.741 3.391 4.209 (58.7%) (60.3%) (51.6%) (74.4%) (70.2%) (63.3%) (26.6%) (18.3%) (20.0%) (12.8%) (18.6%) (14.3%) (18.0%) (19.7%) (23.7%) (35.7%) (25.1%) (0.6%) 0.038 0.047 0.036 0.773 0.756 0.720 0.926 0.607 0.581 0.127 0.205 0.137 0.413 0.457 0.567 2.112 1.629 0.048 0.005 (7.1%) 0.004 (5.6%) 0.006 (9.1%) 0.043 (4.2%) 0.046 (4.3%) 0.086 (7.6%) 0.100 (2.9%) 0.100 (3.0%) 0.116 (4.0%) 0.019 (1.9%) 0.013 (1.2%) 0.011 (1.1%) 0.017 (0.8%) 0.005 (0.2%) 0.006 (0.2%) 0.361 (6.1%) 0.363 (5.6%) 0.610 (8.2%) (32.3%) (28.3%) (37.5%) (9.6%) (9.7%) (14.2%) (22.3%) (22.1%) (21.4%) (47.2%) (43.0%) (49.8%) (40.4%) (40.5%) (39.1%) (12.0%) (17.2%) (35.0%) 0.021 0.022 0.026 0.100 0.105 0.161 0.777 0.733 0.622 0.468 0.474 0.478 0.926 0.942 0.936 0.710 1.114 2.618 0.040 0.051 0.037 0.896 0.925 0.890 2.602 2.486 2.164 0.505 0.615 0.470 1.351 1.376 1.450 4.852 5.020 4.256 0.026 0.026 0.032 0.143 0.151 0.247 0.877 0.832 0.738 0.487 0.487 0.489 0.944 0.947 0.941 1.071 1.477 3.228 0.006 0.009 0.008 0.166 0.216 0.254 1.776 1.978 1.699 0.397 0.423 0.344 0.956 0.924 0.888 3.101 3.754 4.819 0.060 0.068 0.062 0.873 0.860 0.881 1.704 1.340 1.204 0.595 0.680 0.616 1.339 1.399 1.503 2.822 2.744 2.665 0.066 0.077 0.070 1.039 1.077 1.137 3.479 3.318 2.902 0.992 1.102 0.959 2.294 2.323 2.391 5.923 6.497 7.484 Condenser
Evaporator
Drying ducts
Drying cabinet
HRU
II
IV
V
VI
VII
45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 Compressor I
AVEX C_ d;k AVEN C_ d;k UNEX C_ d;k UNEN C_ d;k
UN C_ d;k ($ h1) AV C_ d;k ($ h1) UN C_ d;k ($ h1) EX C_ d;k ($ h1) EN C_ d;k ($ h1)
C_ d;k ($ h1) Drying temperature ( C) Component #
Table 5 e Results of the cost rate associated with exergy destructions for the HP drying system at different drying air temperatures.
AV C_ d;k ($ h1)
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
biggest proportion of the exergy destruction costs was AV. While the proportion of the AV destruction cost to the total destruction cost at 45 C was 82.0%, it decreased to 56.8% at 55 C (Table 5). The major type of investment costs in the HRU was detected as EN with the proportion ranging from 74.7% to 91.2%. Additionally, the AV destruction costs were calculated as between 46.2% and 52.8% of the overall destruction costs (Table 6). While the exergy destruction costs that were accumulated in another heat exchanger used as the evaporator in the system decreased with increasing drying temperature, 75% of the total exergy destruction costs were AV (Table 5). The EN, UN and UNEN investment costs were a considerable proportion of the overall investment costs with values between 84.3% and 88.6%, 59.0% and 62.4% and 52.6% and 53.8%, respectively (Table 6). The third heat exchanger (condenser) was used to transfer energy from the refrigerant to the drying air. While a substantial proportion of the destruction costs of the condenser were EN (approximately 80%) and AV (approximately 85%), two-thirds and half of the overall investment costs were EN and AV, respectively (Tables 5 and 6). Of the destruction costs that occurred in the drying cabinet, 60% were EN or AV. The UNEX destruction costs were extremely low (less than 1% of the overall value), whereas the AVEX destruction costs were remarkably high being in the range of 36.9%e40.6% of the total destruction costs (Table 5). In addition, almost all the investment costs were EN (Table 6). Briefly, the investment costs would be decreased by structural improvements of the component, whereas the destruction costs would be reduced via optimisation of the drying process. Consequently, optimisation studies focused on the drying process are very important due to the energy and cost efficiency (Erbay & Hepbasli, 2013). The exergy destruction costs in the compressor were a small proportion of the total destruction costs (under 1%) (Table 5). Therefore, improvements concentrated on the destructions occurring in the compressor would have limited importance and the investment costs, which were approximately 85% of the overall costs, should be in the foreground of the improvement actions. However, 30% of the overall investment costs were AV and only 24.6%e25.7% were AVEN (Table 6). Consequently, the actions that would focus on the compressor should be about the structural improvements of the component to reduce investment costs. Although there was some importance of the costs occurred in the drying ducts, 34.7%e38.1% of the overall destruction costs were AVEX (Table 5). On the other hand, the majority of total investment costs were EN, whereas 58.4%e60.0% of them were AVEN (Table 6). In other words, optimisation of the system performance is important to lower the destruction costs by reducing the inefficiencies resulting from the component interactions, while the internal structural improvements are essential to reduce the investment costs.
4.2. Comparison of conventional and advanced exergoeconomic analyses Although the irreversibilities/costs accumulated in the system components can be determined by the conventional exergetic/exergoeconomic analysis, their sources and real
37
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Table 6 e Results of the hourly levelised cost of investments for the HP drying system at different drying air temperatures. #
Component
I
Compressor
II
Condenser
IV
Evaporator
V
Drying ducts
VI
Drying cabinet
VII HRU
EN EX UN AV Drying Z_ T;k ($ h1) Z_ T;k ($ h1) Z_ T;k Z_ T;k 1 temperature ( C) ($ h ) ($ h1)
45 50 55 45 50 55 45 50 55 45 50 55 45 50 55 45 50 55
0.374 0.381 0.367 0.241 0.239 0.225 0.357 0.354 0.340 0.085 0.086 0.087 0.723 0.723 0.723 0.265 0.303 0.324
0.082 0.075 0.089 0.105 0.106 0.121 0.046 0.048 0.063 0.003 0.002 0.002 0.000 0.000 0.000 0.090 0.052 0.032
improvement potentials cannot be exactly established. Using advanced techniques, the effects of the component interactions and technological limitations on the efficiency of the system as well as the real potential for improvements can be estimated (Petrakopoulou et al., 2012). The main performance parameters calculated in this study using the conventional and advanced exergetic/exergoeconomic analyses, such as the exergy efficiency, the total costs and the exergoeconomic factor, are listed in Table 7. There was an increase in the total costs of the HRU with the rise in the drying temperature. However, the AVEN costs dramatically decreased (Table 7). Similar tendencies were detected in the variation of 3 modified and f AVEN . While 3 modified advanced to 99.0%, f AVEN increased to 78.4% at the drying temperature of 55 C (Table 7). Namely, the costs increased and the cost reducing potentials decreased with the rise in the drying temperature. As a consequence, the low temperature drying should be chosen to increase the cost performance of the HRU. While the total costs of the drying cabinet were two-fold higher than those of the condenser, the AVEN total costs of the drying cabinet were lower (Table 7). Likewise, the exergetic efficiencies of the drying cabinet were not so much greater (85.1%e86.5%), although 3 modified values were dramatically high (96.4%e96.9%). The main reason for this was that the losses of the drying process, which were unavoidable, occurred in the drying cabinet. The second lowest 3 modified values were calculated for the condenser (82.4%e84.0%). Moreover, the AVEN total costs of the condenser were higher than that of the evaporator (except for 45 C). These calculated results indicated that the condenser was an important system component with respect to cost reduction. The actions focused on the condenser would cause significant decrease in total costs. Although the total costs accumulated in the condenser were 7% of the overall costs and lower than the total costs of the HRU, the drying cabinet and the evaporator regarding the conventional exergoeconomic analysis, the total costs of the condenser were a considerable proportion of the overall system costs (14.9%e16.0%) by the
0.319 0.322 0.311 0.174 0.176 0.170 0.238 0.246 0.251 0.035 0.034 0.034 0.391 0.391 0.391 0.136 0.136 0.166
0.137 0.135 0.146 0.172 0.170 0.176 0.165 0.156 0.151 0.054 0.055 0.054 0.332 0.332 0.332 0.220 0.220 0.189
AV Z_ T;k ($ h1)
UN Z_ T;k ($ h1) UNEN Z_ T;k
UNEX Z_ T;k
0.262 (57.4%) 0.268 (58.8%) 0.250 (54.8%) 0.121 (35.0%) 0.122 (35.0%) 0.111 (32.0%) 0.211 (52.3%) 0.217 (53.8%) 0.212 (52.6%) 0.033 (37.7%) 0.033 (37.3%) 0.034 (38.0%) 0.391 (54.1%) 0.391 (54.1%) 0.391 (54.1%) 0.101 (28.5%) 0.116 (32.6%) 0.151 (42.5%)
0.058 (12.6%) 0.053 (11.7%) 0.061 (13.3%) 0.053 (15.2%) 0.054 (15.6%) 0.059 (17.2%) 0.027 (6.7%) 0.030 (7.3%) 0.039 (9.8%) 0.001 (1.5%) 0.001 (1.0%) 0.001 (0.8%) 0.000 (0.0%) 0.000 (0.0%) 0.000 (0.0%) 0.034 (9.7%) 0.020 (5.6%) 0.015 (4.2%)
AVEN Z_ T;k
0.112 0.112 0.117 0.120 0.117 0.114 0.146 0.138 0.128 0.052 0.053 0.053 0.332 0.332 0.332 0.164 0.188 0.172
(24.6%) (24.6%) (25.7%) (34.7%) (34.0%) (33.1%) (36.3%) (34.2%) (31.7%) (58.4%) (60.0%) (59.9%) (45.9%) (45.9%) (45.9%) (46.2%) (52.8%) (48.6%)
AVEX Z_ T;k
0.025 0.022 0.028 0.052 0.052 0.061 0.019 0.019 0.024 0.002 0.001 0.001 0.000 0.000 0.000 0.056 0.032 0.017
(5.4%) (4.9%) (6.2%) (15.1%) (15.1%) (17.7%) (4.7%) (4.7%) (5.9%) (2.3%) (1.6%) (1.3%) (0.0%) (0.0%) (0.0%) (15.6%) (9.0%) (4.7%)
advanced exergoeconomic analysis. Namely, advanced exergoeconomic analysis showed that the condenser was the second most important system component (after the HRU) with regard to the potential to reduce total costs of the overall system. Similarly, the total costs occurred in the drying ducts were 5.4%e6.4% of the overall system due to the conventional analysis, whereas the AVEN total costs varied in the range of 3.2% and 4.6%. As a consequence, there are strict limits to the scope to improve the system performance and to reduce the costs due to the recent technological development as 3 modified values were calculated in the range of 99.3% and 99.6% (Table 7).
5.
Conclusions
We have applied the conventional and advanced exergoeconomic analyses to a pilot scale HP food dryer for different drying air temperatures in this study. We have separately analysed the components of the drying system and investigated the effects of the operating temperature on the system components. We may list the main conclusions we drawn from the results of the present study as follows: 1. The most important system component was the HRU regarding the cost accumulation. 2. The experimental results suggested that increase in the inlet drying temperature caused lower costs and higher improvement potentials. 3. Concerning the concept for increasing the efficiencies and decreasing the costs, the condenser was the fourth important system component in the conventional exergy analysis, while the second important component in the advanced exergoeconomic analysis. On the contrary, so few interventions that would cause valuable improvements in the costs can be done to the drying ducts due to the advanced exergoeconomic analysis. 4. It may be concluded that the realistic potential improvements and the priorities, which cannot be obtained from conventional exergy-based analyses only, can be
38
76.6 13.7 18.0 27.9 37.0 78.4 70.7 13.5 18.5 20.6 42.1 10.3 74.5 13.4 13.6 28.9 44.6 7.2 0.15 0.83 0.71 0.19 0.90 0.22 94.4 84.0 94.7 99.6 96.4 99.0 91.8 83.3 94.4 99.3 96.8 72.2 92.9 82.4 91.4 99.5 96.9 65.9
0.15 0.89 1.07 0.18 0.74 2.28
0.16 0.87 0.74 0.26 0.79 1.82
50 C 45 C 55 C 50 C 45 C 55 C 50 C
86.8 23.3 12.2 8.5 23.2 4.5 85.5 24.3 10.8 7.4 23.8 5.2 87.4 25.0 10.4 8.2 24.0 5.7 0.53 1.48 3.31 1.05 3.11 7.84 0.53 1.42 3.72 1.19 3.05 6.85 0.52 1.38 3.88 1.08 3.02 6.28 89.6 76.9 78.0 97.1 86.5 37.6 87.1 77.8 75.4 96.4 85.8 39.5 Compressor Condenser Evaporator Drying ducts Drying cabinet HRU I II IV V VI VII
88.5 77.7 73.9 96.5 85.1 40.8
Component
45 C
50 C
55 C
45 C
50 C
55 C
45 C
50 C
55 C
45 C
AVEN C_ T ($ h1)
(%) 3 modified
f (%) C_ T ($ h1)
Conventional methods
(%) 3
determined to decide about the system components to be modified through the advanced-exergy based approaches. Therefore, the method used in this study may be a useful example to analyse the industrial scale drying systems. 5. Optimisation studies focussing on drying foods in terms of energy and/or cost efficiencies and product quality should be done.
Acknowledgements The authors are grateful for the financial support provided for the project entitled “Design, test and performance evaluation of a gas engine-driven solar assisted band conveyor heat pump drying system” under project no: 106M482 by The Scientific and Technological Research Council of Turkey (TUBITAK). They also thank the reviewers for their valuable comments as well as the Editor for his additional useful comments, which have been used in improving the quality of the article.
references
Item no
Table 7 e Comparison of the results of exergetic and exergoeconomic analyses for conventional and advanced methods.
Advanced methods
f AVEN (%)
55 C
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
AOAC. (1990). In K. Heldrich (Ed.), Official methods of analysis of the association of official analytical chemists (15th ed.). Arlington, Virginia, USA: AOAC. Calvet, S., Gates, R. S., Zhang, G., Estelles, F., Ogink, N. W. M., Pedersen, S., et al. (2013). Measuring gas emissions from livestock buildings: a review on uncertainty analysis and error sources. Biosystems Engineering, 116, 221e231. Çengel, Y. A., & Boles, M. A. (2006). Thermodynamics an engineering approach (5th ed.). NJ, USA: McGraw-Hill. Cziesla, F., Tsatsaronis, G., & Gao, Z. (2006). Avoidable thermodynamic inefficiencies and costs in an externally fired combined cycle power plant. Energy, 31, 1472e1489. Erbay, Z., & Hepbasli, A. (2013). Advanced exergy analysis of a heat pump drying system used in food drying. Drying Technology, 31(7), 802e810. Erbay, Z., & Hepbasli, A. (2014). Application of conventional and advanced exergy analyses to evaluate the performance of a ground-source heat pump (GSHP) dryer used in food drying. Energy Conversion and Management, 78, 499e507. Erbay, Z., & Icier, F. (2010). A review of thin layer drying of foods: theory, modeling and experimental results. Critical Reviews in Food Science and Nutrition, 50(5), 441e464. Erbay, Z., Icier, F., & Hepbasli, A. (2010). Exergetic performance assessment of a pilot-scale heat pump belt conveyor dryer. International Journal of Energy Research, 34(3), 249e264. Hepbasli, A. (2012). Low exergy (LowEx) heating and cooling systems for sustainable buildings and societies. Renewable and Sustainable Energy Reviews, 16(1), 73e104. Hepbasli, A., Erbay, Z., Colak, N., Hancioglu, E., & Icier, F. (2010). Exergetic performance assessment of three different food driers. Proceedings of Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 224(1), 1e12. Holman, J. P. (2001). Experimental methods for engineers (7th ed.). Singapore: McGraw Hill. Jangam, S. V. (2011). An overview of recent developments and some R&D challenges related to drying of foods. Drying Technology, 29(12), 1343e1357. Kelly, S. (2008). Energy systems improvement based on endogenous and exogenous exergy destruction. PhD Thesis. Berlin, Germany: € t Berlin. Institut fu¨r Energietechnik, Technische Universta
b i o s y s t e m s e n g i n e e r i n g 1 2 4 ( 2 0 1 4 ) 2 9 e3 9
Kelly, S., Tsatsaronis, G., & Morosuk, T. (2009). Advanced exergetic analysis: approaches for splitting the exergy destruction into endogenous and exogenous parts. Energy, 34, 384e391. Keçebas‚, A., & Hepbasli, A. (2014). Conventional and advanced exergoeconomic analyses of geothermal district heating systems. Energy and Buildings, 69, 434e441. Kotas, T. J. (1995). The exergy method of thermal power plant analysis. Malabar, Florida: Krieger Publishing Company. Kudra, T. (2004). Energy aspects in drying. Drying Technology, 22(5), 917e932. Lazzaretto, A., & Tsatsaronis, G. (2006). SPECO: a systematic and general methodology for calculating efficiencies and costs in thermal systems. Energy, 31, 1257e1289. Minea, V. (2013). Heat-pump-assisted drying: recent technological advances and R&D needs. Drying Technology, 31(10), 1177e1189. Morosuk, T., & Tsatsaronis, G. (2008). A new approach to the exergy analysis of absorbtion refrigeration machines. Energy, 33, 890e907. Morosuk, T., & Tsatsaronis, G. (2009). Advanced exergetic evaluation of refrigeration machines using different working fluids. Energy, 34, 2248e2258. Morosuk, T., Tsatsaronis, G., Boyano, A., & Gantiva, C. (2012). Advanced exergy-based analyses applied to a system including LNG regasification and electricity generation. International Journal of Energy and Environmental Engineering, 3, 1. Morosuk, T., Tsatsaronis, G., & Zhang, C. (2012). Conventional thermodynamic and advanced exergetic analysis of a refrigeration machine using a Voorhees' compression process. Energy Conversion and Management, 60, 143e151. Mujumdar, A. S. (2006). Handbook of industrial drying (3rd ed.). Boca Raton, FL: CRC Press. Petrakopoulou, F., Tsatsaronis, G., Morosuk, T., & Carassai, A. (2012). Conventional and advanced exergetic analyses applied to a combined cycle power plant. Energy, 146e152. Ramaswamy, R., Balasubramaniam, V. M., & Sastry, S. K. (2007). Thermal conductivity of selected liquid foods at elevated pressures up to 700 MPa. Journal of Food Engineering, 83(3), 444e451. Sahoo, P. K. (2008). Exergoeconomic analysis and optimization of a cogeneration system using evolutionary programming. Applied Thermal Engineering, 28, 1580e1588.
39
Shi, Q. L., Xue, C. H., Zhao, Y., Li, Z. J., Wang, X. Y., & Luan, D. L. (2008). Optimization of processing parameters of horse mackerel (Trachurus japonicus) dried in a heat pump dehumidifier using response surface methodology. Journal of Food Engineering, 87, 74e81. € ylemez, M. S. (2006). Optimum heat pump in drying systems So with waste heat recovery. Journal of Food Engineering, 74(3), 292e298. Tarhan, S. (2007). Selection of chemical and thermal pretreatment combination for plum drying at low and moderate drying air temperatures. Journal of Food Engineering, 79, 255e260. Tong, Y., Kozai, T., Nishioka, N., & Ohyama, K. (2010). Greenhouse heating using heat pumps with a high coefficient of performance (COP). Biosystems Engineering, 106, 405e411. Tsatsaronis, G., & Morosuk, T. (2008). A general exergy-based method for combining a cost analysis with an environmental impact analysis, Part I e theoretical Development. In Proceedings of IMECE2008, 2008 ASME International Mechanical Engineering Congress and Exposition, Boston, Massachusetts, USA (pp. 453e462). Tsatsaronis, G., & Morosuk, T. (2009). Understanding and improving energy conversion processes with the aid of exergy-based methods. In 1st International Exergy, Life Cycle Assessment, and Sustainability Workshop and Symposium (ELCAS), Nisyros, Greece. Tsatsaronis, G., & Morosuk, T. (2010). Advanced exergetic analysis of a novel system for generating electricity and vaporizing liquefied natural gas. Energy, 35, 820e829. Vadivambal, R., & Jayas, D. S. (2007). Changes in quality of microwave-treated agricultural products: a review. Biosystems Engineering, 98, 1e16. Yamamura, M., Ohara, K., Mawatari, Y., & Kage, H. (2009). Measuring the drying rate of liquid film coatings using heat flux method. Drying Technology, 27(6), 817e820. Zielinska, M., Zapotoczny, P., Alves-Filho, O., Eikevik, T. M., & Blaszczak, W. (2013). A multi-stage combined heat pump and microwave vacuum drying of green peas. Journal of Food Engineering, 115(3), 347e356.