Development and analysis of a solar and wind energy based multigeneration system

Available online at www.sciencedirect.com

ScienceDirect Solar Energy 122 (2015) 1279–1295 www.elsevier.com/locate/solener

Development and analysis of a solar and wind energy based multigeneration system Sinan Ozlu ⇑, Ibrahim Dincer Department of Mechanical Engineering, University of Ontario Institute of Technology, 2000 Simcoe Street North, L1H 7K4 Oshawa, Ontario, Canada Received 11 April 2015; received in revised form 6 October 2015; accepted 13 October 2015

Communicated by: Associate Editor Mukund Patel

Abstract This paper concerns development and analysis of a solar-wind hybrid multigeneration system. Energy, exergy, exergoeconomic and exergoenvironmental analyses are performed. The analysis studies are undertaken by developing and constructing the codes in Engineering Equation Solver software. The effects of various input conditions on the system performance are investigated through both energy and exergy efficiencies, and an optimization study is undertaken of system efficiency and power output are obtained. The average number of Toronto suites that the system can supply is calculated. As a result, it is seen that energy and exergy efficiencies are higher than equivalent single energy systems. The system has 43% maximum energy efficiency and 65% maximum exergy efficiency. Maximum turbine output is 48 kW, while cooling effect is 28 kW and heating effect is 298.5 kW. There is resultant savings of 1614 tons of CO2 per year by the system. This multigeneration system is capable of supplying at least at a minimum 49 suites. Ó 2015 Elsevier Ltd. All rights reserved.

Keywords: Solar energy; Wind energy; Hybrid; Absorption chiller; Rankine cycle; Renewable energy

1. Introduction Renewable energy sources (solar, wind, etc.) are attracting more attention as alternative energy sources to conventional fossil fuel energy sources. This is not only due to the diminishing fuel sources, but also due to environmental pollution and global warming problems (El-Shatter et al., 2002). Renewable energy sources are the only clean and continuous energy solution to satisfy current and future requirements. A system that can utilize more than three sources is called a multigeneration energy system. The efficiency of multigeneration systems are higher than the combined efficiency of separate units. Multigeneration systems that use renewable sources combine the power of clean ⇑ Corresponding author.

E-mail address: [email protected] (S. Ozlu). http://dx.doi.org/10.1016/j.solener.2015.10.035 0038-092X/Ó 2015 Elsevier Ltd. All rights reserved.

energy with high efficiency. Moreover, they help to supply different needs of a public unit such as a multi-suite building or a neighborhood. One of the main challenges in this subject is the lack of study, especially a totally renewable based multigeneration energy system to produce electricity, cooling, heating, hot water and hydrogen simultaneously. This has made the proposed system quite interesting. Efforts to develop more efficient multienergy systems, attracts many researchers. Another challenge is the scheduling and modeling of the sources, solar and wind in this case. Solar energy is not constant, the intensity changes during the day and throughout the year. There is no sun at all at night. Moreover, neither wind presence nor wind speed is a factor that can be guaranteed. The problem can be simplified by making some assumptions such as taking the average solar intensity and wind speed.

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Nomenclature A c C D E_ x F F0 g G h k L m m_ P Q Q_ s S S_ t T U V W W_ z

area, m2 specific heat, kJ/kgK power coefficient diameter, m exergy rate, kW view factor collector efficiency factor gravitational acceleration, 9.81 m/s2 solar radiation rate, W/m2 specific enthalpy, kJ/kg; heat transfer coefficient, W/m2 K conductivity of the absorber tube material, W/ mK length, m mass, kg mass flow rate, kg/s pressure, kPa heat, kJ heat transfer rate, kW specific entropy, kJ/kg absorbed solar radiation per unit aperture area, W/m2 entropy rate, kW time, s temperature, K heat transfer coefficient, W/m2 K velocity, m/s work, kJ; width, m work rate, kW elevation, m

Subscripts abs absorption ap aperture con condenser cs cold storage cv control volume d destructed dwh domestic water heater

The amount of solar energy that reaches earth’s upper atmosphere is about 1350 W/m2. The atmosphere reflects, scatters and absorbs some of the energy. In Canada, depending on sky conditions, peak solar intensity varies from about 900 W/m2 to 1050 W/m2. Peak solar intensity is at solar noon, when the sun is due south (Cengel et al., 2011). The amount of the sun’s energy reaching the surface of the earth also depends on cloud cover, air pollution, location and the time of year. An active solar system uses mechanical equipment to collect, store and distribute heat from the sun. Active systems consist of solar collectors, a storage medium and a distribution system. Active solar

e en eva ex exp gen hs hx i L p Q r rc sc t ts u w wt 0 1. . .70

exit stream energy evaporator exergy expander generator hot storage heat exchanger inlet overall pump; pressure heat receiver; Rankine ammonia–water Rankine cycle solar cycle; solar collector tube thermal storage unshaded; useful wind; water wind turbine ambient or reference condition state numbers

Greek letters a absorptivity g efficiency n insulation thickness, m q density, kg/m3; specular reflectance of the concentrator s effect of angle of incidence Acronyms COP coefficient of performance EES Engineering Equation Solver ORC Organic Rankine Cycle PR pump pressure ratio PV photovoltaic

systems are commonly used for; water heating, space conditioning, producing electricity, processing heat and solar mechanical energy. When higher temperatures are required, concentrated solar collectors are used. Solar energy falling on a large reflective surface is reflected onto a smaller area before it is converted into heat. This is done so that the surface absorbing the concentrated energy is smaller than the surface capturing the energy and as a result can attain higher temperatures before heat loss due to radiation and the convection wastes of the energy that has been collected (Pavlas et al., 2006).

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295

Ahmadi et al. (2014) designed and optimized a novel solar-based multigeneration energy system. They used ocean thermal energy conversion which uses a heat engine for harvesting energy from the ocean. In order to produce electricity a heat engine operates between the relatively warm ocean surface, which is exposed to the sun, and the colder (about 5 °C) water deeper in the ocean. They found that the best optimized point from the multi-objective optimization has an exergy efficiency of 60%, while the total cost rate of the system at this point is 154 $/h. Ratlamwala et al. (2012) proposed an integrated system, consisting of a heliostat field, a steam cycle, an ORC and an electrolyzer for hydrogen production. The results showed that the power and rate of hydrogen production increased with an increase in the heliostat field area and solar flux. The optimization study yielded maximum energy and exergy efficiencies and the rate of hydrogen production was 18.74%, 39.6% and 1.57 m3/s respectively. Ozturk and Dincer (2013) worked on a renewable based multigeneration energy production system producing a number of outputs, such as power, heating, cooling, hot water, hydrogen and oxygen. The solar based multigeneration system with an exergy efficiency of 57.4% was obtained. This was higher than using the sub-systems separately. The parabolic dish collectors had the highest exergy destruction rate among constituent parts of the solar based multigeneration system, due to a high temperature difference between the working fluid and collector receivers. Xu et al. (2011) made an energy and exergy analysis of the solar power tower system using molten salt as the heat transfer fluid. They evaluated both the energy and exergy losses in each component and in the overall system to identify the causes and locations of the thermodynamic imperfections. Wang et al. (2009) proposed a new combined cooling, heating and power system driven by solar energy. The system combines a Rankine cycle and an ejector refrigeration cycle, which could produce cooling output, heating output and power output simultaneously. Since the oil crises of the early 1970, utilization of solar and wind power has become increasingly significant, attractive and cost-effective. However, a common drawback with solar and wind energy is their unpredictable nature. Standalone photovoltaic (PV) or wind energy systems do not produce usable energy for a significant portion of time during the year. In the former case this is mainly due to dependence on sunshine hours, which are variable and on relatively high cut-in wind speeds, which range from 3.5 to 4.5 m/s, in the latter case, resulting in an underutilization of capacity. In general, the variations of solar and wind energy do not match with the time distribution of demand. The independent use of the systems results in considerable over-sizing for system reliability, which in turn makes the design costly. As the advantages of solar and wind energy systems became widely known, system designers have started looking toward their integration (Desmukh and Desmukh, 2008). The term hybrid

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renewable energy system is used to describe any energy system with more than one type of energy source (compared to systems which use only one source of alternative energy) to lower costs and increase reliability. Celik (2003) addressed the sizing and techno-economic optimization of an autonomous PV–wind hybrid energy system with battery storage. The level of autonomy, i.e. the fraction of time for which the specified load can be met, and the cost of the system, were his design parameters. He showed that the worst month scenarios resulted in too costly results, so he suggested an alternative solution to incorporate a third energy source into the system. Notton et al. (2011) showed that a precise study of renewable energy potential is indispensable before implementing a renewable energy system. The solar and wind energy potential is presented for five sites distributed in a Mediterranean island and the temporal complementary of these two energy resources is discussed. Caliskan et al. (2013) performed exergoeconomic and environmental impact analyses, through energy, exergy and sustainability assessment methods to investigate a hybrid wind–solar based hydrogen and electricity production system. Kaabeche et al. (2011) proposed an integrated PV–wind hybrid system optimization model, which utilizes the iterative optimization technique following the deficiency and power supply probability, the relative excess power generated, the total net present cost, the total annualized cost and break-even distance analysis for power reliability and system costs. Syed et al. (2009) studied the effect that the integration of the hybrid photovoltaic/wind turbine generation can have on conservation of energy and reduction of greenhouse gases. They calculated base-case energy demands using building energy simulation software. Tina and Gagliano (2011) reported, as a method of evaluating, a procedure for the probabilistic treatment of solar irradiance and wind speed data. Their results informed the design of a pre-processing stage for the input of an algorithm that probabilistically optimizes the design of hybrid solar wind power systems. The previous studies on solar and hybrid systems discussed in this section help building the model for the proposed system. The objective of studying the proposed system is to create a hybrid system that can use multiple sources as substitutes which have multiple outcomes hence maximizing the efficiency. Solar-wind hybrid systems are studied as these two sources complement each other in that if one is deficient or inactive the other system comes into effect. Optimization of the system, by studying the behavior of solar and wind energy, has been the main focus of the researchers in this subject. Focus of attention has increased in recent times on solar energy based multigeneration systems and as a result more research is being conducted on these systems every year. This should result in finding new techniques, increase in the efficiencies and a decrease in operating costs.

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Fig. 1. Configuration of the system.

The multigeneration system studied is a hybrid system using both solar and wind energy. It utilizes both energy sources efficiently because the extra energy is saved in the hot storage tank and hydrogen tank. During nighttime or when there is not strong enough wind, this extra energy can be used. The system configuration is shown in Fig. 1. The thermodynamic analysis is based on some assumptions and input data. The assumptions for the system are as follows:

 Electrolyzer operates with 60% efficiency (Ahmadi, 2013).  There are no pressure changes except through flow restrictors and pump.  System is in steady state.  Wind turbine operates with 90% efficiency (Duffie and Beckman, 2006).  Wind turbine operates with the average Toronto wind speed.  States at points 1, 4, 8 are saturated liquid.  State at point 10 is saturated vapor.

 Heat losses from the system boundaries are negligible.  Possible sources of data noise, e.g. sudden changes in solar irradiance and electric power demand, are not considered in the analyses (i.e. average hourly values are used).  The solar collector operates during the day and stores heat in the thermal storage units, then uses this energy during the night.  The turbine operate with 70% efficiency (Ahmadi, 2013).  The pumps operate with 85% efficiency (Ahmadi, 2013).

Input parameters for modeling the system are shown in Table 1. These parameters have to be set at commencement in order to perform the other calculations. Main objective of the multigeneration system studied is to produce domestic heating, cooling, electricity and hydrogen for a multi-unit building. The system is designed to meet the energy needs of a multi-suite facility. A secondary objective is to see the interaction of different systems with each other, such as solar energy, wind energy, Rankine cycle, Absorption chiller, electrolyzer etc. and

2. System description

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295 Table 1 Input parameters used to model the system. Collector Width Length Absorber diameter Transparent envelope outer diameter Tube material Receiver efficiency Solar system working fluid

2m 2m 25 mm 40 mm Stainless steel 75% Therminol 66

Thermal storage Insulation thickness Insulation material Total surface area

30 cm Polyurethane 6 m2

Rankine cycle Working fluid

Ammonia–water

Wind turbine Diameter Average wind speed Power coefficient

34 m 4.2 m/s 60%

Absorption chiller Evaporator temperature Condenser temperature Absorber temperature Generator temperature

7 °C 35 °C 40 °C 80 °C

suggest the optimum conditions in which they should be combined. The configuration of the system lets the Rankine system makes optimum use of the energy coming from the solar collectors. The waste heat from the cycle is used for obtaining hot water and cooling is by means of the absorption chiller. In this system, the solar energy is collected by a parabolic solar collector. Working fluid is Therminol 66. Hot working fluid (35) is transferred to the hot storage tank to be used when there is not enough sun. From the storage tank it passes through to the boiler (29–30) to heat the ammonia–water mixture in the Rankine cycle (20–21). The evaporated mixture is expanded (21–22) to produce work. Waste heat from the expander is used to heat domestic water (26–27) in the condenser. The pump is used to pressurize the mixture (19–20). The mechanical energy produced is converted to electrical energy by means of a turbine and a generator. The rest of the solar energy is initially used in domestic heating (30–17). Subsequently, it is used in the generator of an absorption chiller for cooling purposes. The inlet temperature of the generator (17) should be at least 120 °C in order to run the absorption cooling system. The absorption chiller uses heat instead of mechanical energy, to provide cooling. The mechanical vapor compressor is replaced by a thermal compressor that consists of an absorber, a generator, a pump, and a throttling device. Refrigerant is ammonia in the cycle (7–8–9– 10). Absorbent is water in the cycle (1–2–3–4–5–6). The ammonia vapor from the evaporator (10) is absorbed by the absorber water (6–1). This solution is then pumped to the generator where the refrigerant is revaporized (3–4) using the remaining solar energy heat source. The ammonia depleted solution is then returned to the absorber via a throttling device (5–6). The electricity produced by the

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ammonia–water Rankine cycle turbine can be used in residences when there is extra energy or to run the electrolyzer to produce hydrogen. Wind turbine also produces electricity when there is enough wind. This electricity is also used in the building or, if there is extra energy, in an electrolyzer to produce hydrogen. The modeling of the system is performed using in the Engineering Equation Solver software. The system is a hybrid, stand-alone, renewable, multigeneration system. 3. Analysis This section outlines the model development and analyses carried out in this paper. In the beginning, thermodynamic and exergy analyses are introduced. Then the environmental analysis is performed. The optimization approach is explained next. Finally it is shown how electrical and heat loads are calculated. 3.1. Thermodynamic analyses In order to analyze a control volume, four things need to be considered; mass balance, energy balance, entropy balance and exergy balance. By writing these equations for each system and subsystem, equations can be solved correctly. 3.1.1. Mass balance equation According to the conservation of mass principle, the net mass transfer to or from a control volume during time interval Dt is equal to the mass entering the control volume minus mass exiting the control volume (Cengel et al., 2011) as shown in the equation below: m_ in  m_ out ¼

dmcv dt

ð1Þ

where m_ in and m_ out are the mass flow rate of inlet and outlet. 3.1.2. Energy balance equation According to the First Law of Thermodynamics, energy is conserved. When this principle is considered for a steady flow system and a control volume, the following equation is obtained:  X  V2 Q_ in þ W_ in þ þ gz m_ h þ 2 in   X V2 _ _ ¼ Qout þ W out þ þ gz ð2Þ m_ h þ 2 out where Q_ is heat transfer rate, W_ is work rate, h is specific enthalpy, m_ is velocity, g is gravitational acceleration, and z is the elevation. 3.1.3. Entropy balance equation There is an increase in the sum of the entropies of the participating systems according to the Second Law of

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Thermodynamics. Entropy balance equation applied to a control volume can be expressed as S_ gen ¼

X

m_ e se 

X

m_ i si 

X Q_ k

dS CV þ Tk dt

ð3Þ

where e denotes exit, i denotes inlet, Q_ is heat transfer rate, s is the entropy. Positive direction of heat transfer is to the system. 3.1.4. Exergy balance equation When an exergy analysis is performed, the thermodynamic imperfections can be quantified as exergy destructions, which represent losses in energy quality or usefulness (Dincer and Rosen, 2012). The exergy of a substance is often in 4 different forms: physical, chemical, kinetic and potential energy. The last 2 forms are assumed to be negligible as elevation changes are small and speeds are low. In addition, chemical energy is not considered as solar energy is used as a source. According to second law of Thermodynamics, exergy balance equation can be written as X X _ Qþ _ W þ Ex _ D Ex ð4Þ m_ i exi ¼ m_ e exe þ Ex i

e

where subscripts i and e denote the control volume inlet _ D is the exergy destrucand outlet flow respectively and Ex tion rate. Other terms are explained as: _ W is the exergy transfer associated with mechanical Ex _ W ¼ W_ . _ W is shown as Ex work. The equation of Ex _ExQ is the exergy transfer associated with heat transfer and it depends on the temperature at which it occurs in relation to the temperature of the environment (Caliskan et al., _ Q is shown as Ex _ Q ¼ ð1  T 0 ÞQ_ i . 2013). The equation of Ex Ti where T0 is the ambient temperature, Ti is the temperature of the heat transferred to the boundary of the control volume and Q_ i is the heat transfer to the control volume. After introducing general equations, the equations for each component in the system are shown. In order to solve the unknown parameters of the system, each component should be solved on a one by one basis, before proceeding to the next one in order to arrive at a solution. 3.1.5. Thermodynamic analyses of system components  Parabolic solar collector A parabolic collector can accept both beam and diffuse radiation because of its large acceptance angle. Actual useful energy gain in the collector is expressed as (Duffie and Beckman, 2006):   Ar Qu ¼ F R Au S  U L ðT 34  T 0 Þ ð5Þ Ao where Au is the unshaded area of the concentrator aperture (m2), Ar is the area of the receiver (m2), S is the absorbed solar radiation per unit of aperture area (W/m2) and can be found from:

S ¼ I ap sqa

ð6Þ

where I ap is the effective incident radiation measured on the plane of the aperture (W/m2), s is the effect of angle of incidence, q is the specular reflectance of the concentrator. F R can be found from the following equation:    _ p Ar U L F 0 mc 1  exp FR ¼ ð7Þ _ p Ar U L mC where m_ is the mass flow rate of the heating fluid (kg/s), cp is the specific heat of the heating fluid (kJ/kg K), U L is the overall heat transfer coefficient (W/m2 K). F 0 can be found from the following equation: F0 ¼

1 UL 1 UL

þ hDt Do i þ



Do 2k

ln DDoi



ð8Þ

where ht is the heat transfer coefficient inside the tube (W/ m2 K), Di is the absorber inside diameter (m), k is the conductivity of the absorber tube material (W/m K).  Hot storage If an insulation of thickness n (m) and thermal conductivity k (W/m K) is used, the coefficient of heat transfer U (W/m2 K) between the working fluid and air is given by 1 1 n ¼ þ U h k

ð9Þ

where h is the coefficient of heat transfer from working fluid to air (W/m2 K). The corresponding hot storage heat loss Q_ hs (W/m2) per unit area of the surface of the tank is given by Q_ hs ¼ U ðT 35  T 0 Þ. where T 35 is the temperature of the fluid entering the hot thermal storage (K) and T 0 is the atmospheric temperature. The recommended type of insulation is 20 cm mineral wool insulation (Desmukh and Desmukh, 2008). If all the parameters are the same, cold storage heat loss can be found by inserting T 18 instead of T 35 . where T 18 is the temperature of the fluid entering the cold thermal storage (K).  Domestic water heater The hot gases from the ammonia–water Rankine cycle boiler enter the water heater to warm domestic hot water to 60 °C. Water enters this heater at atmospheric pressure and ambient temperature. The energy balance for this component is given as follows: m_ sc ðh30  h17 Þ ¼ m_ w ðh32  h31 Þ

ð10Þ

 Absorption chiller The rate of heat to the generator of an absorption system is provided using solar energy and calculated using the following equation: Q_ gen ¼ m_ sc ðh17  h18 Þ

ð11Þ

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295

where m_ sc is the mass flow rate of the working fluid in the solar cycle (kg/s). In order to obtain the outlet conditions of the generator, the following equation is used: m_ 3 h3 þ Q_ gen ¼ m_ 4 h4 þ m_ 7 h7

ð12Þ

The mass balance equations for the heat exchanger are given as: m_ 2 ¼ m_ 3 and m_ 4 ¼ m_ 5 . The energy balance equation for heat exchanges is given below: m_ 2 ðh3  h2 Þ ¼ m_ 4 ðh4  h5 Þ

ð13Þ

The mass balance equation for the condenser is given as m_ 7 ¼ m_ 8 . The energy balance equation for the condenser is given below: m_ 8 h8 þ Q_ con ¼ m_ 7 h7

ð14Þ

The equation for mass balances for the evaporator is given as m_ 9 ¼ m_ 10 . The equation for energy balance for the evaporator can be written as follows: m_ 9 h9 þ Q_ eva ¼ m_ 10 h10

ð15Þ

The energy balance equation that is used to calculate the heat rejected from the absorber is as follows: m_ 6 h6 þ m_ 10 h10 ¼ m_ 1 h1 þ Q_ abs

ð16Þ

The work done by the pump is calculated using the equation given below: W_ p ¼ m_ 1 ðh2  h1 Þ

ð17Þ

The energetic COP is found using the following equation: COP en ¼

Q_ eva _Qgen þ W_ p

ð18Þ

The exergetic COP can be expressed as follows: COP ex ¼

_ eva Ex _ gen þ W_ p Ex

ð19Þ

 Rankine cycle The power that can be obtained from the cycle is defined as: W_ t;rc ¼ m_ rc ðh21  h22 Þ

ð20Þ

gex ¼

W_ net;rc _ boiler;rc Ex

ð21Þ

The rate of heat rejected by the condenser is defined as: Q_ con;rc ¼ m_ rc ðh22  h19 Þ

ð22Þ

The energy efficiency of ammonia–water Rankine cycle is defined as: gen ¼

W_ net;rc Q_ boiler;rc

ð23Þ

The exergy efficiency of ammonia–water Rankine cycle can be expressed as follows:

ð24Þ

 Wind turbine Average power obtained from the wind turbine is expressed as follows (Duffie and Beckman, 2006): 1 P w ¼ gwt qair Awt C p V 3 2

ð25Þ

where gwt is the wind turbine efficiency, qair is the air density (kg/m3), Awt is the wind turbine area (m2), C p is the turbine power coefficient, V is the average velocity of the wind (m2/ s). Exergy efficiency of the wind turbine is: gex ¼

W_ wt _ wt Ex

ð26Þ

_ wt is the exergy of the wind turbine and calculated where Ex as: _ wt ¼ 1 qair Awt V 3 Ex 2

ð27Þ

3.2. Exergy analysis For exergy analysis, exergy destruction in each component of the system, energy and exergy efficiency equations are introduced here. 3.2.1. Exergy balance equations The exergy destructions for basic components in the system are listed in Table 2. The expressions are based on state points shown in Fig. 1. Exergy of each state point can be calculated using EES software based on state pressure and temperature. 3.2.2. Energy efficiency Energy efficiency is defined as the ratio of useful energy produced to the input energy supplied to the system. In the system, energy efficiencies of ammonia–water Rankine cycle can be calculated by the following formula:

The power consumed by pump is expressed as: W_ p;rc ¼ m_ rc ðh20  h19 Þ

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gen;rc ¼

W_ exp  W_ p;rc Q_ boiler

ð28Þ

System efficiency equation can be expressed as follows: gen;system ¼

W_ exp þ W_ wind  W_ p;solar  W_ p;rc Q_ solar þ W_ wind

ð29Þ

Also energy coefficient of performance for the absorption chiller can be calculated as follows: COP en;chiller ¼

Q_ eva Q_ gen þ W_ p

ð30Þ

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Table 2 Exergy destruction rates of components in the system. Component

Exergy destruction rate expression

Parabolic solar collector Hot storage Cold storage Domestic water heater

_ 34  Ex _ 35 _ d;sc ¼ Q_ solar ð1  T 0 Þ þ Ex Ex T sun _ d;hs ¼ Ex _ 35  Ex _ 29  Ex _ Q Ex _ d;cs ¼ Ex _ 18  Ex _ 33  Ex _ Q Ex _ d;dwh ¼ Ex _ 30  Ex _ 17 þ Ex _ 31  Ex _ Ex    32          _Exd;sc ¼ Q_ solar 1  T 0  Q_ dwh 1  T 0  Q_ boiler 1  T 0  Q_ gen 1  T 0  Q_ hs 1  T 0  Q_ cs 1  T 0  W_ p;solar T sun T dwh T boiler T gen T hs T cs

Solar cycle Absorption Absorption Absorption Absorption Absorption Absorption Absorption Absorption

_ d;gen ¼ Ex _ 3  Ex _ 4  Ex _ 7 þ Ex _ 17  Ex _ 18 Ex _ d;con ¼ Ex _ 7  Ex _ 8 þ Ex _ 13  Ex _ 14 Ex _ d;valve ¼ Ex _ 8  Ex _ 9 Ex _ d;eva ¼ Ex _ 9  Ex _ 10 þ Ex _ 11  Ex _ 12 Ex _ d;abs ¼ Ex _ 10 þ Ex _ 6  Ex _ 1 þ Ex _ 15  Ex _ 16 Ex _ d;p ¼ Ex _ 1  Ex _ 2 þ W_ p;abs Ex _ d;throttle ¼ Ex _ 5  Ex _ 6 Ex _ d;hx ¼ Ex _ 2  Ex _ 3 þ Ex _ 4  Ex _ 5 Ex     T 0 _ d;abs ¼ Q_ gen 1   Q_ eva 1  T 0  W_ p;abs Ex

generator condenser expansion valve evaporator absorber pump throttling valve heat exchanger

Absorption cycle

T gen

Boiler Ammonia–water Rankine pump Ammonia–water Rankine condenser Expander Ammonia–water Rankine cycle Wind turbine

T eva

_ d;boiler ¼ Ex _ 20  Ex _ 21 þ Ex _ 29  Ex _ 30 Ex _ d;p rc ¼ Ex _ 19  Ex _ 20 þ W_ p;rc Ex _ d;rc con ¼ Ex _ 22  Ex _ 19 þ Ex _ 26  Ex _ 27 Ex _ d;exp ¼ Ex _ 21  Ex _ 22 Ex     _ d;rc ¼ Q_ boiler 1  T 0  Q_ con 1  T 0 þ W_ exp  W_ p;rc Ex T boiler T con   _ d;wt ¼ 1  1  W_ wt Ex C p;wt

Table 3 Average emissions from US power plants. Source: United States Environmental Protection Agency Clear Energy (2015).

Natural gas Coal Oil

CO2 (kg/MW h)

SO2 (kg/MW h)

NOx (kg/MW h)

515.00 1020.00 758.00

0.04 6.00 5.00

0.77 3.00 2.00

Exergy coefficient of performance for the absorption chiller can be calculated as follows:   Q_ eva 1  TTeva0   ð34Þ COP ex;chiller ¼ Q_ gen 1  TTgen0 þ W_ p 3.3. Environmental analysis

3.2.3. Exergy efficiency Exergy efficiency is the product exergy output divided by the exergy input. Solar system exergy efficiency formula can be written as follows:       T0 0 Qboiler 1  T boiler þ Qgen 1  TTgen0 þ Qdwh 1  TTdwh   gex;sc ¼ Q_ solar 1  TTsun0 ð31Þ Exergy efficiency of the Rankine cycle can be expressed as follows:   W exp  W p;rc þ Qcon 1  TTcon0 gex;rc ¼ ð32Þ Qboiler System exergy efficiency is defined as follows:

gex;system

Air polluting emissions such as nitrogen oxides (NOx), carbon dioxide (CO2), sulfur dioxide (SO2), methane (CH4), and mercury (Hg) compounds associated with generating electricity, heat and hydrogen from solar technologies are negligible because no fuels are combusted. As there is no pollution caused by these systems, air emissions from fossil fuel fired power plants with an equivalent power output can be calculated and saved emissions can be determined (Dincer et al., 2013). According to the United States Environmental Protection Agency, average emissions emitted by power plants with respect to the fuel are shown in Table 3. As natural gas is widely used in North America, calculations are based on the usage of natural gas. Environmental analysis is made based on the emissions produced using fossil fuels to achieve the same results.

      0 W_ exp þ Q_ con 1  TTcon0 þ Q_ eva 1  TTeva0 þ Q_ dwh 1  TTdwh þ W_ wt  W_ p;sc  W_ p;rc   ¼ 3 q A V Q_ solar 1  TTsun0 þ air wt2 wind

ð33Þ

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3.4. Optimization

Table 4 Building characteristics of units considered. Source: Binkley (2012).

Optimization is maximizing or minimizing an objective function by manipulating with the independent variables considering the constraints and the boundaries. In this section, the main parameters of optimization such as objective function, decision variables, bounds and trial and error values are introduced.

Average Average Average Average Average

3.4.1. Objective function Objective function is the variable to be minimized or maximized depending on the targets of the decision maker. In multigeneration systems objective function can be as follows:  Efficiency (energy, exergy etc.).  Cost (investment, annualized costs, cost of exergy destruction etc.).  Emitted pollutants (CO2, SO2, NOx etc.). If more than one objective is chosen, it is called multiobjective optimization (Dincer and Rosen, 2012). 3.4.2. Decision variables Decision variables are the variables that affect the objective function. It is necessary to select as many independent variables as there are degrees of freedom. However only the most important variables with a major effect should be chosen. Examples for the decision variables are solar radiation, ambient temperature, number of solar units, condenser outlet temperature, pump pressure ratio etc. 3.4.3. Bounds Each independent variable requires lower and upper bounds. These bounds are specified for the following properties:  Dimensions or weight of the system.  Highest temperature that fluids and the components are used having regard to safety.  Highest pressure allowed by the fluids and the components.  Maximum flow rate of the working fluids.  Minimum temperature that the components or working fluids can operate.

3.4.4. Selecting value(s) Choosing (by trial and error) the correct value(s) improve the likelihood of finding an optimum. Incorrect selection may result in it taking too long or even be impossible, for the program to converge into a solution. 3.5. Estimation of heating, cooling, electricity loads When designing multigeneration systems, it is important to determine the target of the output. The systems designed

number of storeys per building number of suites per building date of construction gross floor area per building (m2) attributed suite area (m2)

13 188 1984 18,400 104

in this paper are for a Toronto multi-unit residential building. The building characteristics considered are in Table 4. The average energy intensities per suite and per building are shown in Table 5. Energy intensity is a building’s annual energy consumption per unit of gross floor area. The table shows that the annual energy needed to heat a suite in Toronto in equivalent kW h. Natural gas consumption in cubic meters is used to find the energy intensity. The conversion from cubic meters of natural gas supplied to equivalent kilowatt-hours of energy was based on a factor of 37.08 MJ/m3 or 10.3 kW h/m3 (Binkley, 2012). According to Binkley (2012), the average end-use distribution for Toronto buildings is 38% electricity, 37% space heating (30% electricity and 70% natural gas), and 25% domestic hot water. The annual energy intensity is based on the total annual energy consumed from both electric and natural gas sources divided by the building’s gross floor area. The ratio of electricity is 38% and natural gas is 62%. In order to calculate the percentage of electricity for cooling, historical data related to degree days for Toronto was obtained from Toronto Hydro (2015). The average annual degree days for heating for Toronto between 2001 and 2013 were 3638, whereas average annual degree days for cooling was 380. As a result the cooling load is 10% of heating load. By sharing the energy intensity to loads based on the percentages, the loads in equivalent annual kW h in Table 6 are found. 4. Results and discussion In this section system results are analyzed. This is done by laying out comparison graphs and optimizing the system parameters. 4.1. Thermodynamic modeling results The results obtained from the system are tabulated in Table 7. These outputs are subject to change depending on the parameter that is under consideration. For maximum efficiency, efficiency may increase while other parameters would drop. This is discussed in optimization section. The exergy destruction for the main components of the system are shown in Fig. 2. The last column shows the total exergy destruction in the system. Highest exergy destruction occurs in the solar system while the lowest is in the absorption chiller. This means that due to irreversibilities, 251 kW of energy is lost in

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Table 5 Annual natural gas intensity of a suite in Toronto. Source: Binkley (2012). Annual value per suite (ekW h)

295

25,100

Electricity (cooling + the rest) Space heating Domestic hot water

Annual value per suite (ekW h)

112 (11 + 101) 109 74

9538 (929 + 8609) 9287 6275

298.5 28 48 43 65 1.96 0.26 0.80 0.31 1613 485

600

Exergy Destrucon Rate (kW)

ex (N=4)

0.3 0.25

0.15 200

500 400 300 200 100

Rankine cycle

Wind Turbine

Domesc Water

System

Fig. 2. Exergy destructions in the system.

the wind turbine and 485 kW is lost in the system. An exergy destruction graph is a useful to tool to focus on the sources of irreversibilities. It is shown in Fig. 3 that the effect of solar radiation on a number of solar units and corresponding the efficiency levels. When there are 2 solar units installed, both system energy and exergy efficiencies drop radically, they stabilize after around 800 W/m2. The reason for this is that solar radiation increases but the output does not increase at the same rate as the solar radiation. When there are 4 solar units installed, both energy and exergy efficiencies are lower compared to 2 solar units for low solar radiation. Efficiencies for 4 units are greater than that for 2 units after 600

300

400

500

600

700

800

900

1000

Solar radiaon (W/m2)

Fig. 3. System energy and exergy efficiencies vs. solar radiation.

0.34 0.32

en

ex

0.3

Efficiency

Q_ heating (kW) Q_ cooling;absorption (kW) Maximum W_ turbine (kW) Maximum gmulti (%) Maximum wmulti (%) m_ H2 (kg/h) m_ dwh (kg/s) Absorption chiller COP en Absorption chiller COP ex CO2 emissions saved (tons/year) Total exergy destruction rate (kW)

Solar system Absorpon Chiller

en (N=4)

0.2

Annual value per m2 (ekW h/m2)

Table 7 Parameter values resulting from energy and exergy analyses of the system.

0

ex (N=2)

0.35

Table 6 Design loads of the system. Load

en (N=2)

0.4

Efficiency

Natural gas energy intensity

Annual value per m2 (ekW h/m2)

0.45

0.28 0.26 0.24 0.22 0.2

10

15

20

25

30

35

40

45

50

T0 (°C)

Fig. 4. System energy and exergy efficiencies vs. ambient temperature.

and 700 W/m2 for exergy and energy efficiencies respectively. The reason for this phenomena is that when there are 4 solar units installed, for higher solar radiation the increase in output is much higher than 2 solar units compared to the increase in solar heat input. Ambient temperature (T0) affects system energy and exergy efficiencies indirectly in Fig. 4. Energy efficiency drops because the increase in the output is lower than the increase in solar energy. Exergy efficiency drops at a faster rate because it is more affected by the increase in ambient temperature. As reference temperature increases, the temperature difference of the process temperature drops. If the process temperature does not increase at the same rate as the reference temperature, the exergy value drops. As it is shown in Fig. 5, the pressure ratio of the Rankine cycle pump affects the Rankine cycle and system efficiencies. System efficiencies increase at the same rate with increasing pressure ratio. However, while Rankine cycle exergy efficiency increases at a faster rate, energy efficiency increases even more so, then stabilizes at a value of 10% after a pressure ratio of 20. The reason for the fast rate of increase in the Rankine cycle energy efficiency at low pressure ratios is that by increasing pressure ratio, the increase in output drops and stabilizes. The reason for the slower rate of increase in exergy efficiency is because heat output from the Rankine cycle drops. However, as the work output increase surpasses heat output increase, the efficiency increases. According to Fig. 6, by increasing boiler outlet temperature all the efficiencies drop. The drop is more significant

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295

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ex,rankine

en,system

Efficiency

0.4

0.3

0.2

0.1

0

32

ex,system

Rankine Cycle Heat Output (kW)

en,rankine

2

7

12

17

Qout

270

30 250

28

230

26

210

24

190

22

170

20

150 100

22

Wout

120

140

160

Rankine Cycle Work Output (kW)

290 0.5

18 200

180

Boiler Outlet Temperature (°C)

Pressure Rao

Fig. 5. System and Rankine cycle efficiencies vs. Rankine cycle pump pressure ratio.

Fig. 7. Rankine cycle heat and work outputs vs. boiler outlet temperature.

1

ex,system

en,rankine

0.6 0.5 0.4

0.2 0.1 0

1

2

3

4

5

6

7

Rankine cycle mass flow rate (kg/s)

Fig. 8. System and Rankine cycle efficiencies vs. Rankine cycle mass flow rate.

has to work harder to pump high mass flow rate fluid. The increase in work output is not as high as work input as a result Rankine cycle energy and exergy efficiencies drop. In Fig. 9 the system and solar system energy and exergy efficiencies versus solar system mass flow rate are analyzed. All the efficiencies drop with an increasing mass flow rate of the solar system. The most significant drop is in solar

ex,rankine

en,system

ex,system

ex,solar

0.3 0.25

Efficiency

0.7

Efficiency

ex,rankine

0.3

0.8 0.6 0.5 0.4

0.2 0.15 0.1

0.3

0.05

0.2 0.1 0 100

en,rankine

0.7

0.35 en,system

ex,system

0.8

1 0.9

en,system

0.9

Efficiency

in Rankine cycle exergy efficiency, then in system exergy efficiency. System energy and exergy efficiencies are affected negatively because heat output from the Rankine system drops. Although heat output to the domestic water heater increases, this increase is not enough to increase the efficiency. The reason for the drop in Rankine cycle efficiencies is due to the decrease in work and heat outputs from the Rankine system. Both work output and heat output from the Rankine cycle are negatively affected by an increase in boiler outlet temperature as seen in Fig. 7. When the boiler outlet temperature increases, less heat is transferred to the Rankine cycle, hence reducing the heat and work outputs from the system. The reason for the irregularity in the work output graph is because the amount of data is not sufficient to make the curve smooth. If larger amount of data is taken to plot the graph, it would be a smooth curve. It is shown in Fig. 8 that when the mass flow rate of the Rankine cycle is increased, the energy and exergy efficiency of Rankine cycle drops while system energy and exergy efficiencies increase. The rate of increase is the same in system efficiencies while rate of drop is higher in Rankine cycle exergy efficiency than energy efficiency. The reason for the drop in Rankine cycle efficiencies is pump work input increases when the mass flow rate increases. The pump

0 0.5 120

140

160

180

200

1.5

2.5

3.5

4.5

Solar System Mass Flow Rate(kg/s)

Boiler Outlet Temperature (°C)

Fig. 6. System and Rankine cycle efficiencies vs. boiler outlet temperature.

Fig. 9. System and solar system efficiencies vs. solar system mass flow rate.

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295 1 COP_en

0.9

COP_ex

en,system

ex,system

0.8 0.7

COP/Efficiencies

system and system exergy efficiencies, followed by solar system energy efficiency. All the graphs are parabolic with the rate of drop decreasing. Efficiencies decrease because the pump in the solar system has to work much harder to pump working fluid. As a result, work input in the system increases but the output heat and work do not increase at the same rate as the work input. The reason that solar system exergy efficiency drops faster than system efficiencies is that solar system exergy increases at a much higher rate than the system efficiency parameters. Cold storage outlet temperature affects the efficiencies. All the efficiencies increase with increasing outlet temperature as shown in Fig. 10. The effect is more significant in the solar system exergy efficiency. The rate of increase of solar system efficiency is much higher than system efficiencies because the heat input to the Rankine cycle increases at a high rate (which is an output for the solar cycle). The rate of increase is the same in system efficiencies. System efficiencies increase because of the increase of work and heat output from Rankine cycle. It is shown in Fig. 11 that the energy coefficient of performance (COP) of absorption chiller increases with increasing evaporator temperature while exergy COP drops. Energy COP straight-lines after 18 °C. System energy efficiency stays constant while system exergy efficiency decreases slightly. The reason for the increase of energy COP is due to the increase in evaporator heat input with increasing evaporator temperature. Exergy COP decreases because evaporator temperature is an effective factor for exergy COP calculation. Numerator is Q_ eva ð1  TTeva0 Þ for COP exergy calculation. Because of the increase in evaporator temperature, heat output from the evaporator increases, and exergy COP decreases. All the COPs and efficiencies drop with increasing absorption chiller condenser temperature as Fig. 12 shows. The drop is more significant for the COPs while efficiencies are almost constant, dropping slightly. The highest drop is in the energy COP. Because of the output of the absorption chiller, evaporator heat drops at a faster rate. The drop for the exergy COP is slower that energy COP because, during the calculation of exergy COP, evaporator heat is multiplied by a factor which reduces the decrease rate.

0.6 0.5 0.4 0.3 0.2 0.1 0

5

7

9

11

13

15

17

19

Absorpon Chiller Evaporator Temperature(°C)

Fig. 11. Absorption chiller COPs and system efficiencies vs. absorption chiller evaporator temperature.

1 COP_en

0.9

COP_ex

en,system

ex,system

0.8

COP/Efficiencies

1290

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

25

27

29

31

33

35

37

39

Absorpon Chiller Condenser Temperature(°C)

Fig. 12. Absorption chiller COPs and system efficiencies vs. absorption chiller condenser temperature.

All the COPs and efficiencies drop by increasing absorption chiller absorber temperature as shown in Fig. 13. The graphs are exactly the same as absorption chiller condenser temperature graphs with a shift of 5 °C. The drop is more significant for the COPs while efficiencies are almost constant, dropping slightly. The highest drop is in the energy COP because evaporator heat (which is the output of the absorption chiller), drops at a faster rate. The drop for the exergy COP is slower than energy COP because during

1

0.34

en,system

ex,system

0.32

COP_ex

en,system

ex,system

0.8

COP/Efficiencies

0.3

Efficiency

COP_en

0.9

ex,solar

0.28 0.26 0.24

0.7 0.6 0.5 0.4 0.3 0.2

0.22 0.2

0.1

10

15

20

25

30

35

40

45

50

Cold Storage Outlet Temperature(°C)

Fig. 10. System and solar cycle efficiencies vs. cold storage outlet temperature.

0 30

32

34

36

38

40

42

44

Absorpon Chiller Absorber Temperature(°C)

Fig. 13. Absorption chiller COPs and system efficiencies vs. absorption chiller absorber temperature.

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295

the calculation of exergy COP, evaporator heat is multiplied by a factor which reduces the drop rate. As it is shown in Fig. 14, all the parameters except energy COP increase with the increasing absorption chiller generator temperature. The changes are not very significant for efficiencies while COPs change more significantly. Energy COP increases because evaporator heat input increases. Exergy COP drops because as generator temperature increases, the denominator also increases, thereby decreasing the fraction. 4.2. Optimization results In this section significant output parameters are tested for optimization by finding the appropriate values of the input parameters. Optimization is done by EES Min/Max property. The function to be maximized is the power output from the Rankine cycle. The independent variables, system bounds, optimum values and maximum power output are listed in Table 8. Minimum and maximum values for each variable are determined based on physical limits. After running the maximization property of EES, the result is achieved by solving 330 equations by 199 iterations in 10.9 s. Maximum number of iterations is set initially to have the opportunity to abort the optimization if an optimum value is not found in a specific time. The results show that for a solar system flow rate of 1.38 kg/s, Rankine cycle pressure ratio of 100, ambient temperature of 50 °C, boiler output temperature of 100 °C, solar radiation of 1000 W/ m2, the power output is maximized at 47.75 kW. System energy and exergy efficiency are the parameters that have to be maximized. Five independent variables that have an effect on the efficiency are chosen as shown in Table 9. These are; solar radiation, solar cycle mass flow rate, ambient temperature, Rankine cycle pressure ratio and boiler exit temperature. These variables are input values of the model created in EES. Minimum and maximum values of these variables can also be seen in Table 9. The value of the variables to reach maximum efficiency in the system are in the ‘‘Opt gen ” column in Table 9. The last row shows the result of the energy efficiency

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Table 8 Independent variables of the system for power output maximization. Variable 2

Solar radiation, G (W/m ) Ambient temperature, T0 (°C) Rankine cycle pressure ratio, PR Solar cycle mass flow rate, m_ oil (kg/s) Boiler exit temperature, T30 (°C) Maximum power output (kW)

Min

Max

Opt

0 0 2 0.50 100

1000 50 100 5.00 150

1000 50 100 1.38 100 47.75

optimization. Maximum energy efficiency of the system is 43.2% if the parameters are chosen as shown in Table 9. In order to check maximum exergy efficiency of the system, another run is performed. The optimum variables are shown in Table 9 in ‘‘Opt gex ” column. The maximum value of exergy efficiency is 65% for the system. 4.3. Environmental impact assessment results It is shown in Table 3 that natural gas produces 515 kg/ MW h CO2, 0.04 kg/MW h SO2 and 0.77 kg/MW h NOx. As shown in Table 7, heating load is 298.5 kW, cooling load is 28 kW and maximum power output from the turbine is 48 kW, also shown in the optimization section. When these three outputs are added, total output of the system is found as 375.5 kW. The system saves heat in the thermal storage and assumed to work 24 h/day and 365 days/year. So the annual output becomes 3289 MW h. If the same output is obtained from a plant that works by natural gas, 1694 tons of CO2 would be emitted. It can be calculate that 131 kg of SO2 and 2.5 tons of NOx is emitted as well. Natural gas is the source that produces less emissions than coal or oil. The amount of greenhouse gases saved instead of using natural gas, coal and oil are shown in Table 10. 4.4. Loading results This system is designed to supply a multi-unit building. The average load for an average Toronto, Ontario suite is used in the calculations. The cooling load obtained from the system is 28 kW. This makes 245.3 MW h/year. According to Table 5, this much load is enough to supply a 264 suite building. When the power output is considered, it can be shown by the same method that the system can supply 49 units. The heating load is used for two purposes; space heating and domestic hot water. When these two are combined, it can be seen that there is enough load for a 168 suite building. The results are shown in Table 11. 4.5. Comparison with experiment results

Fig. 14. Absorption chiller COPs and system efficiencies vs. absorption chiller generator temperature.

In order to compare theoretical results with experimental data, a trigeneration system setup designed and built by Tarique (2014) is used. The studied system has outputs the same as the experimental setup. The calculations of the

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Table 9 Independent variables of the system for efficiency maximization. Variable 2

Solar radiation, G (W/m ) Solar cycle mass flow rate, m_ oil (kg/s) Ambient temperature, T0 (°C) Rankine cycle pressure ratio, PR Boiler exit temperature, T30 (°C) Maximum efficiency

Min

Max

Opt gen

Opt gex

0 0.500 10 1 100

1000 5.000 35 100 150

100 1.989 10 20 100 43:2%

660 1.989 10 1 100 65%

Table 10 Emissions saved if fossil fuels were used.

Natural gas Coal Oil

CO2 (tons/year)

SO2 (tons/year)

NOx (tons/year)

1694.00 3355.00 2493.00

0.13 20.00 16.00

2.50 10.00 7.00

Table 11 Number of suites supplied by the system based on loads. Load

Number of suites supplied

Cooling Electricity except cooling Space heating + domestic hot water

264 49 109

initial and final conditions in the system are compared with the experimental results. The results of the experiments are important and provide a deeper understanding of the

Table 12 Ammonia–water based trigeneration system with Rankine and ejector cycle integration. Source: Tarique (2014). Process

Description

1–2 2–3 3–4–5 5–6–15

Pressurization of liquid (pumping) Preheating (regenerator) Vapor generation Flow splitting of superheated vapor (#5 toward expander, #15 toward ejector) 6–7 Vapor expansion 7–8 Regeneration (heat release from two-phase flow) 8–9–16 Mixing of streams #8 and #16 9–10 Ammonia resorption and incomplete condensation 10–11 Complete condensation and heat rejection 11–1–12 Liquid flow splitting (#1 toward pump, #12 toward throttling valve) 13–14 Evaporation and heat absorption from cooling process 14–15–16 Ejector process (14–16 compression, 15–16 expansion) 17–18 Cold liquid injection for lubrication

Fig. 15. Simplified version of ammonia – water based trigeneration system (adapted from Tarique (2014)).

S. Ozlu, I. Dincer / Solar Energy 122 (2015) 1279–1295 Table 13 Performance comparison of experimental system with the proposed system. Source: Tarique (2014). Quantity

Experimental system

Proposed system

Net generated work Generated heat Generated cooling Heat input Energy input Generated heat exergy Exergy of cooling effect Energetic COP Exergetic COP

69.1 kJ/kg (2.6%) 1930 kJ/kg (73%) 226 kJ/kg (11%) 2105 kJ/kg 537.1 kJ/kg 176 kJ/kg (8.4%) 19.13 kJ/kg (1%) 1.06 0.49

21.83 kJ/kg (6.2%) 53.39 kJ/kg (15%) 27.94 kJ/kg (8%) 331 kJ/kg 17.37 kJ/kg 9 kJ/kg (2.7%) 1.8 (0.5%) 0.80 0.31

processes. This also allows for validation of the thermodynamic analysis results. In order to utilize low-grade heat to generate power, cooling effect and hot water, a test bench is being built. The trigeneration system uses ammonia–water as a working fluid. The test bench consists of an expander, an air cooled condenser, a compressor, an evaporator, shell and tube heat exchanger, and auxiliary components. This integrated system combines power and cooling cycles, where the source heat is used to generate power through a scroll expander and a portion of the heat is used in an ejector cooling system. The residual heat, which is normally

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released to the environment in this type of power cycle, is captured for hot water heating or space heating (Tarique, 2014). A simplified version of the experimental setup is shown in Fig. 15. Black arrows signify heat fluxes, gray arrow signifies cooling and white arrow signifies power. The processes in the system are explained in Table 12. The comparison of the outputs from the experimental setup and the system designed is shown in Table 13. As the quantity of the inputs (heat inputs) are different, each result is given as a percentage of the heat input. Due to unprocessed data, efficiencies, heat losses and different system configurations, the results do not match. In the proposed system, energy is distributed to system components in different proportions. Heating, cooling, electricity or other outputs can be favored depending on the application. The same system can be run to demonstrate different outputs. This is one of the reasons that the output of the system and experimental setup do not necessarily match. The proposed system and the experimental setup have similar outputs but with some major changes. For example in the proposed system wind energy and electrolyzer differ from the experimental setup. In addition, in the experimental setup, there is a quadruple effect absorption chiller which is different than a single effect absorption chiller. System input parameters other than

Fig. 16. Similar multigeneration system (adapted from Ozturk and Dincer (2013)).

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heat input can be adjusted to achieve the same result as the experimental results. 4.6. Comparison with similar system Ozturk and Dincer (2013) studied a system similar to the one under review. The differences between the systems are the lack of wind energy supply and an additional Rankine cycle. A comparison of the two systems is performed in this section. The system reviewed by Ozturk and Dincer (2013) produces a number of outputs, such as power, heating, cooling, hot water, hydrogen and oxygen. The solar-based multi-generation system consists of four main subsystems: Rankine cycle, organic Rankine cycle, absorption cooling and heating, and hydrogen production and utilization. They carried out exergy destruction ratios and rates, power or heat transfer rates, energy and exergy efficiencies of the system components. The system is shown in Fig. 16. According to the analysis, this system’s exergy efficiency varies between 55% and 58%, where the exergy destruction rate varies between 9500 and 12,000 kW in the ambient temperature of 10–30 °C. The exergy efficiency of the proposed system at the same temperatures varies between 29% and 32% which is lower than the system being used for comparison purposes. The system has a maximum energy efficiency of 52.82% and a maximum exergy efficiency of 57.39% whereas the proposed system has a maximum energy efficiency of 43% and a maximum exergy efficiency of 65% as summarized in Table 7. The results of the two systems are similar, especially the maximum system efficiency values. The reasons for the differences are different configurations of the systems, assumptions and the calculation methods. 5. Conclusions This study focuses on developing a novel multigeneration energy system using solar and wind energy to meet all the energy requirements of a multi-unit building. In order to provide a comparison with deeper detail, this system is considered for performance assessment. Exergy and environmental impact analysis of the system is conducted to gain a better insight into this study. In the system, solar energy is used to produce electricity, domestic heating water, cooling and hydrogen. There is a wind turbine to supply the system and measure the effects. The system utilizes a Rankine cycle, absorption chiller and electrolyzer. This system has 43% maximum energy efficiency and 65% maximum exergy efficiency. Maximum turbine output is 48 kW, while cooling effect is 28 kW and heating effect is 298.5 kW. 1614 tons per year of CO2 is saved by the system. It is capable of supplying at least 49 suites. The systems are compared with the outputs of a trigeneration system developed in the lab. Due to the unprocessed data and different outputs, the results do not

match 100%. However, it is seen that by using a multigeneration system, efficiency is higher than the combined efficiency of a system with separate units. With the assistance of this study, the same or similar system can be built and used to achieve higher efficiencies by using renewable sources to serve multi-unit buildings or districts. The future energy solutions have to contain renewable sources as an alternative to fossil fuels. Other similar hybrid energy generating systems can be analyzed with a fair degree of accuracy using the proposed technique. The results of this thesis should be used to design new multigeneration systems or develop these systems to achieve better results in the future. References Ahmadi, P., 2013. Modeling, analysis and optimization of integrated energy systems for multigeneration purposes. Ph.D. Thesis. Faculty of Engineering and Applied Science, UOIT, Oshawa, Ontario. Ahmadi, P., Dincer, P., Rosen, M.A., 2014. Multi-objective optimization of a novel solar-based multigeneration energy system. Sol. Energy 108, 576–591. Binkley, C., 2012. Energy consumption tends of multi-unit residential buildings in the city of Toronto. M.Sc. Thesis, Department of Civil Engineering, University of Toronto, Toronto, Ontario Caliskan, H., Dincer, I., Hepbasli, A., 2013. Exergoeconomic and environmental impact analyses of a renewable energy based hydrogen production system. Int. J. Hydrogen Energy, 1–8. Celik, A.N., 2003. Techno-economic analysis of autonomous PV–wind hybrid energy systems using different sizing methods. Energy Convers. Manage. 44, 1951–1968. Cengel, Y.A., Boles, M.A., Kanog˘lu, M., 2011. Thermodynamics: an engineering approach. McGraw-Hill, New York. Desmukh, M.K., Desmukh, S.S., 2008. Modeling of hybrid renewable energy systems. Renew. Sustain. Energy Rev. 12, 235–249. Dincer, I., Rosen, M.A., 2012. Exergy Energy Environment and Sustainable Development. Elsevier Science. Dincer, I., Colpan, C.O., Kadioglu, F., 2013. Causes Impacts and Solutions to Global Warming. Springer, New York. Duffie, J.A., Beckman, W.A., 2006. Solar Engineering of Thermal Processes. John Wiley & Sons Inc.. El-Shatter, T.F., Eskandar, M.N., El-Hagry, M.T., 2002. Hybrid PV/fuel cell system design and simulation. Renew Energy 27, 479–485. Kaabeche, A., Belhamel, M., Ibtiouen, R., 2011. Techno-economic valuation and optimization of integrated photovoltaic/wind energy conversion system. Sol. Energy 85, 2407–2420. Notton, G., Diaf, S., Stoyanov, L., 2011. Hybrid photovoltaic/wind energy systems for remote locations. Energy Procedia 6, 666–677. Pavlas, M., Stehlı´k, P., Oral, J., Sˇikula, J., 2006. Integrating renewable sources of energy into an existing combined heat and power system. Energy 31 (13), 2499–2511. Ratlamwala, T.A.H., Dincer, I., Aydin, M., 2012. Energy and exergy analyses and optimization study of an integrated solar heliostat field system for hydrogen production. Int. J. Hydrogen Energy 37, 18704– 18712. Ozturk, M., Dincer, I., 2013. Thermodynamic analysis of a solar-based multi-generation system with hydrogen production. Appl. Therm. Eng. 51, 1235–1244. Syed, A.M., Fung, A.S., Ugursal, V.I., Taherian, H., 2009. Analysis of PV/wind potential in the Canadian residential sector through high-resolution building energy simulation. Int. J. Energy Res. 33, 342–357. Tarique, M.A., 2014, Design, analysis and experimental investigation of a new scroll expander based tri-generation system. Ph.D. Thesis, Faculty of Engineering and Applied Science, UOIT, Oshawa, Ontario.

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