Thermo-economic assessment of hybrid renewable energy based cooling system for food preservation in hilly terrain

Thermo-economic assessment of hybrid renewable energy based cooling system for food preservation in hilly terrain

Renewable Energy 87 (2016) 493e500 Contents lists available at ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene Ther...

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Renewable Energy 87 (2016) 493e500

Contents lists available at ScienceDirect

Renewable Energy journal homepage: www.elsevier.com/locate/renene

Thermo-economic assessment of hybrid renewable energy based cooling system for food preservation in hilly terrain M. Edwin a, *, S. Joseph Sekhar b a b

Department of Mechanical Engineering, University College of Engineering, Nagercoil, Anna University Constituent College, Nagercoil, India Department of Mechanical Engineering, St. Xavier's Catholic College of Engineering, Chunkankadai, Nagercoil, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 February 2015 Received in revised form 30 September 2015 Accepted 27 October 2015 Available online xxx

In the commercial food sector, preservation and transportation is responsible to avoid the 22% spoilage of the total food production in developing countries like India. To reduce the spoilage, preservation of such produce including milk is needed in remote places. Due to the increased fossil fuel costs, issues in grid extension and environmental concerns, there has been a renewed interest in hybrid renewable energy systems for cooling applications in remote/rural areas. In this paper, the overall thermal performance and economic aspects of a hybrid energy based milk cooling system for hilly terrain have been analysed using the MATLAB software and the appropriate hybrid energy systems has been predicted. The results indicate that the biomass and gobar gas combination can show the overall thermal performance as 0.17e0.23 with lowest Payback period and life cycle cost of 4.5 years and INR 2.8  107 respectively. The sensitivity analysis shows that the maximum influence of uncertainty in input parameters on the overall COP, capital cost, running cost and payback period are 6.8, 5.1, 5.3 and 6.1 percentages respectively. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Bio-energy Hybrid energy Payback period Net present value Life cycle cost

1. Introduction Milk and agro processing has a potentially important role in the economic development of developing countries. In the Indian context, milk has a special role to play for its many nutritional advantages besides providing supplementary income to 70 million farmers in remote villages [1]. However, 20e25% of the total milk production is spoiled due to improper preservation [2]. This may be a great loss to the farmers and the country. The spoilage can be reduced by implementing suitable preservation strategies in the places where it is produced [3,4]. The major approved methods of milk preservation are refrigeration and/or heat treatment, although both methods have limitations with respect to processing [5]. Fresh milk, after milking, normally has a temperature of 33  C. Proper milk cooling is essential to ensure good quality, because bacteria multiply rapidly when milk is cooled too slowly or if it is stored at temperatures above 4  C. Cooling and storage is very important, especially if there is a long delay (more than 2 h) between milking and delivery at the collection center. In such cases, ideal storage temperature is 1e2  C.

* Corresponding author. E-mail address: [email protected] (M. Edwin). http://dx.doi.org/10.1016/j.renene.2015.10.056 0960-1481/© 2015 Elsevier Ltd. All rights reserved.

Cooling should be done in two stages. First, fresh milk is pre-cooled to 15e20  C or lower. Then, it is cooled to storage temperature. For any subsequent milk (arriving in batches) the mixed or blended temperature should not go above 10  C [6]. The vapor compression refrigeration system working with conventional energy has been used for most of the cooling applications. In recent years, the focus of the nations is shifted to renewable energy technologies because of the issues associated with conventional sources of energy. If the cooling facility is located near the raw materials, the post-harvest losses can be minimized. In remote places, farmers use salting and drying for food preservation, and due to the unhygienic methods used, the spoilage is very high [7]. Some places the preservation of fruits and vegetables is done by mixing chemical preservatives and antioxidants [8]. Non-availability of cooling or chilling system and high ambient temperature are the main constrains in milk collection and distribution. These conditions decrease or shorten the shelf life of raw milk [9]. The problems related to milk marketing include lack of quality control, lack of cooling and storage facilities, poor quality of milk supplied from rural areas, sale of raw milk, inappropriate handling and storage vessels, gap in the cold chain and transport facilities, and spoilage due to lack of preservation and processing facilities [10,11]. The studies conducted on a biomass-based sorption cold storage

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Nomenclature m T CV Q

h d

mass flow rate, kg s1 temperature,  C calorific value, kJ kg1 heat transfer rate, kW efficiency annual interest rate

Abbreviations COP coefficient of performance HR hilly region GG gobar gas source BG biogas source BM biomass source VARS vapour absorption refrigeration system VCRS vapour compression refrigeration system TR tonne of refrigeration CC capital cost (INR) RC running cost (INR)

system of capacity 15 MT [12] show that the operating cost is 25e30% lower than that of the conventional cooling system for the same capacity. The research conducted on solar powered cooling system for food preservation in rural areas also shows that the COP can be maintained between 0.45 and 0.65 with the payback period of 4.5e6 years [13e16]. Biogas based cooling system minimizes the exergetic manufacturing cost, which is normally very high for conventional energy based cooling system [17]. Unfortunately, any single renewable energy source could not provide a continuous power supply due to variations in weather and climate conditions. So the combination of two or more energy sources can improve the power supply reliability by using the complementary characteristics of other energy sources [18]. During low solar radiation, other renewable energy is integrated with solar energy, which gives better COP [19]. Effective and optimum use of the energy sources in stand-alone systems can help in meeting the energy demands of remote, inaccessible areas and make them self sufficient [20]. The hybrid renewable energy based systems are mainly used in the power generation sector because it has an excellent solution for electrification of remote areas [21] where the grid extension is noneconomical. The photovoltaic/diesel hybrid energy system with battery backup is a good alternative energy source for dieselpowered generator, and it has high energy potential and low carbon emission at affordable cost of electricity [22e24]. The hydrowind hybrid energy system can be used in remote areas with the nominal unit cost of electricity [25]. Hybrid system will become an increasingly attractive option as the cost of solar thermal falls, and the prices of feedstock, fossil fuel and land continue to rise [26]. Hybrid energy systems with suitable combination of renewable energy sources can possess the advantages of both systems. Thus reduction in implementation and maintenance cost, improvement in reliability, techno-economic viability and environmental friendliness etc., could be achieved [27e29]. A Cogeneration plant based on the biogas can be hybridized with auxiliary solar energy source, having the advantage of financial incentives [30]. Biomasssolar hybrid energy based absorption cooling system could extend the evaporator's operation time [31]. Wind-biomass and Biomasssolar- Hydel based hybrid energy systems are very good alternatives for the wind-diesel system, because of their attractive energy price [32]. Solar-wind hybrid energy system has the lowest value of

PBP NPV LCC PWC RE SV HES INR

payback period (years) net present value (INR) life cycle cost (INR) present worth cost (INR) replacement cost (INR) salvage value hybrid energy system Indian rupee (1 USD ¼ INR 62.5)

Subscripts m milk e evaporator i inlet o outlet ch chiller c conversion os overall system g generator t total n life time (years)

levelised cost, operating cost, net present cost, life cycle cost and emission [33]. The overall efficiency of the system is increased with the payback period of 8 years when the biomass and fuel cell energies are combined [34]. The life cycle cost, life cycle unit cost and the present worth cost of waste heat operated cooling system is lower than that of presently operated conventional cooling systems [35]. From the review of the literature, it is seen that most of the investigations on the hybrid renewable energy systems focuses on the production of electrical energy. However limited studies are reported on the feasibility of hybrid energy operated cooling systems in remote areas. The studies conducted by the authors' [36,37] on rubber, paddy and sea shore regions to apply hybrid energy based cooling system for food preservation shows that the conventional energy based cooling system can be retrofitted with hybrid renewable energy. To further extend the study for the implementation of hybrid energy based cooling systems in remote hilly regions, additional survey was conducted. The data on the availability of biomass, biogas and gobar gas energy sources have been studied. The possibility of combining these energy sources to meet the total cooling requirement for the preservation of milk, which is produced in the hilly region, has been studied and the various thermo-economic parameters are analysed and presented in this paper. 2. Selection of hybrid energy system for hilly region (HR) To utilize the available energy sources efficiently in remote places, a study has been conducted in few remote hilly villages situated in the southern part of India. The photographical view taken from the study area of hilly regions are shown in Fig. 1. Data pertaining to the available energy resources, energy consumption pattern and current usage of renewable energy sources in the study area are collected with appropriate questionnaires. The important observations from the survey are given in Table 1. The major biomass energy sources identified are, tapioca stem, coconut shell, wood chips, wood pellets etc. Similarly the biogas and gobar gas sources are calculated from the quantity of municipal solid wastes, population of cows, cattle, buffalos and goats. Milk, fruits, agro produce and bio-waste obtained from livestock are calculated from the survey.

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495

Fig. 1. Photographical view of remote Hilly Region.

Table 1 Details of survey data in remote hilly terrains. Particulars

Survey details

Particulars

Survey details

No of villages Total population (Nos) Density of livestock population (Nos) Biomass sources (kg/day) Gobar gas sources (kg/day)

5 1450 130 360e600 610e780

Geographical area of the region No of households (Nos) Quantity of dung production (kg/day) Biogas sources (kg/day) Quantity of milk production (Lt/day)

22 sq km 378 690 600e900 1600

3. System description The schematic diagram of a proposed hybrid energy system which consists of two major sub-systems is shown in Fig. 2. 1. Energy conversion system: It converts the energy available in the feedstock to thermal energy for heating the generator of a VARS. The various conversion devices such as biomass gasifier, biogas plant and gobar gas plant have been used. One are more of these devices are selected based on their availability and the cooling load requirement. 2. Vapour absorption refrigeration system: Either the LiBr-water or aqua ammonia system can be used as the cooling device. The total cooling load for the milk cooling is taken from the refrigeration effect of the VARS. The cooling load is calculated based on the per day requirement of cooling water which can cool the total milk, produced in a day, from 32  C to 4  C, within 4 h [38,39]. In the biomass gasifier, wood chips, tapioca stem, etc., are used as energy crops. In the biogas plant, municipal solid waste and food waste from houses are the sources of energy. In the gobar gas plant, cow dung is used as an energy crop. In the vapour absorption

BM, BG & GG

Energy conversion system (BM gasifier, BG plant & GG plant )

Cooling Load (Qe)

VARS Generator

Evaporator

Fig. 2. Schematic diagram of a Hybrid energy based cooling system.

system aqua ammonia refrigeranteabsorbent pair has been used for the cooling purpose because LiBr-water VARS cannot be operated below 5  C cooling temperature [40,41]. The COP of VARS has been taken as 0.5. The evaporator temperature and generator temperature are taken as 2  Ce12  C and 110  Ce140  C respectively [42]. The COP of the VARS is assumed to calculate the generator heat requirement and based on that the required combinations of energy sources from the availability of biomass, biogas and gobar gas, are selected, and further used in the analysis. The important assumptions are constant calorific values for energy sources, constant conversion efficiency for a particular energy source, stable COP for the vapour absorption system, stable cooling requirement throughout the year, negligible variation in labor cost, properties of milk is constant, and additional expense for diesel due to flexibility in fuel prices is negligible.

4. Mathematical model The steps followed to analyze the hybrid system are represented in a flow chart shown in Fig. 3. The energy generated form each energy source has been calculated, based on the conversion efficiencies of biomass (hc,BM), biogas (hc,BG) and gobar gas (hc,GG), and their values are taken as 0.45, 0.25 and 0.35 respectively [43e45]. The quality and quantity of agro wastes have been estimated based on the available data (Table 1). The heat produced from the biomass gasifier (QBM) can be determined from Refs. [12,46,47].

QBM ¼ mBM  CVBM  hc;BM

(1)

The quantity of solid waste generated per family is taken as 3e6 kg per day [48], The heat produced from the biogas plant (QBG)

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START

Ncows, milk/cow, ρm, Cpm, Tei, Teo, COPch, CVGG, CVBG, CVBM, ηc(GG), ηc(BG), ηc(BM)

Vm = Ncows x milk/cow

mm = Vm x ρm

Availability of Cowdung

Availability of Biowaste

Availability of biomass sources

Calculate mGG

Calculate mBG

Calculate mBM

QGG=mGG x CVGG

QBG=mBG x CVBG

QBM=mBM x CVBM

Qe = mm x Cpm x ΔT

Different Combinations of GG, BG, BM Calculate Qg = QGG + QBG (OR) Calculate Qg = QGG + QBM (OR) Calculate Qg = QBG + QBM

Qg = Qe / COPch

COPOS & Economical Parameters

No

All Combinations are optimised?

Optimal Sizing

Yes

Store the Optimal Parameters

Select the suitable combinations with optimum COPOS & Economical Parameters

Print the suitable combinations END Fig. 3. Flow chart for the optimal hybrid energy system.

is given as [12,46,47].

QBG ¼ mBG  CVBG  hc;BG

Qg ¼ Qe =COP (2)

The biogas production from the cow dung has been worked out, based on the assumption that 4 kge7 kg dung per cow per day is produced [48,49]. The heat produced from the gobar gas plant (QGG) can be obtained from the equation [12,46,47].

QGG ¼ mGG  CVGG  hc;GG

(3)

The evaporator load (Qe) in the steady state condition is obtained from the basic relation [12,46,47].

Qe ¼ m  Cp  DT

(4)

The required quantity of biomass, biogas and gobar gas sources are calculated based on the cooling load requirement and the requirement of thermal load to the generator in the absorption chiller. The cooling load requirement is calculated based on the equation (4). Thermal energy required is calculated based on the cooling load and COP of the vapour absorption cooling system. The quantity of heat supplied to the generator is to be determined by using the following relation [12,46,47].

(5)

where, Qg is the heat supplied to the generator in kW. Assume COP of the absorption chiller is 0.5 [50]. The overall system performance (COPOS) of the proposed system is determined from the equation [46,47].

COPos ¼ Q e =ðx$mBM CVBM þ y$mBG CVBG þ z$mGG CVGG Þ

(6)

where x, y and z denote the proportion of biomass, biogas and gobar gas energy in hybrid energy system. 5. Economical model The capital cost (CC), running cost (RC), payback period (PBP), Annualized Capital Cost (ACC), Total Annual Cost (TAC) and Net Present Value (NPV) are important factors to be considered in the selection of hybrid systems. These economical parameters have been calculated from the authors' previous studies [36,37]. The life cycle cost (LCC) analysis, based on Present Worth Cost (PWC) method, which covers the initial costs, operating costs, maintenance costs, replacement costs and salvage values, is the useful tool to merit various combinations of hybrid energy based cooling system in remote places.

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LCC ¼ Initial capital costs þ PRC þ PRE þ PSV

(7)

A future amount of money for an item converted into its equivalent present value is called the present worth of this item. The following equation is used to calculate the PWC of operating costs and maintenance costs.

PRC ¼ RC$

  ð1 þ dÞn  1 i$ð1 þ dÞn

(8)

The following equation is used to calculate the PWC of replacement costs and salvage values.

 PRE ¼ RE$  PSV ¼ SV$

1 ð1 þ dÞn

1 ð1 þ dÞn

 (9)

 (10)

Here the salvage value of the hybrid energy based absorption system after 18 years is estimated by assuming 7% of total initial costs of the system. The replacement costs of VARS include solution pump, refrigerant pump, cooling water pump, chilled water pump, LT and HT hot water pump. Based on this consideration, the replacement cost of the hybrid energy based absorption system after 18 years is estimated by assuming 1% of total initial costs of the system. The input parameters used in the analysis are available in the previous studies also [36,37]. MATLAB software has been used to simulate the hybrid energy system. To find the COPOS and all the economic parameters such as CC, RC, PBP, LCC, NPV, ACC and TAC of the system, all the components are interconnected as per the real system.

497

In hybrid energy systems, if the number of energy sources is less, the initial cost and system complication could be minimized. So minimum of two energy sources should be combined to meet this required cooling load. Therefore the three energy sources, BM, BG and GG, are combined as BM-BG, BM-GG and BG-GG for this simulation study. In the plots, the ratio of the two energy sources is given in X-axis in such a way that the usage of first energy source increases from left to right whereas the other energy source increases from right to left. Normal operating range denotes that the minimum and maximum availability of BM, BG and GG energy sources. Fig. 5 shows that, the COPOS increases with increase in ratio of energy sources for the BM-GG and BM-BG combinations. This is due to the high heating value of energy sources and the better conversion efficiency of biomass gasifier. Whereas the COPOS decreases with increase in ratio of energy sources for the BG-GG combination. In BM-GG combination, COPOS varies between 0.18 and 0.23. Whereas the other two combinations, BM-BG and BG-GG, show a comparatively low COPOS of 0.13e0.23 and 0.13e0.18 respectively. When the ratio of energy source is above 80%, the COPOS of BM-GG and BM-BG are closer to each other. Therefore any combinations from these two can be used. The BG-GG combination shows that the decrement value of COPOS, so this combination may not be considered in this region. The capital cost and running cost for various combinations with respect to the ratio of energy sources are plotted in Fig. 6. It is observed that the BG-GG combination gives the lowest capital cost, when the GG contribution is at maximum level. When the GG

0.24

Normal Operating Range 0.22 0.2 0.18 0.16 0.14 0.12

BM-BG

BM-GG

BG-GG

0.1 0

0.2

0.4

0.6

0.8

1

Ratio of Energy Sources Fig. 5. Overall performance of the cooling system in HR with various combinations.

7.5

2.4

3000

Available Quantity (kg/day)

2500

Required Quantity (kg/day)

Capital Cost (INR x 1000000)

Quantity of energy sources

3500

2000 1500 1000 500

2.38

BM-BG (CC)

BM-GG (CC)

BG-GG (CC)

BM-BG (RC)

BM-GG (RC)

BG-GG (RC)

7

2.36 6.5

2.34 2.32

6

2.3 5.5

2.28 2.26

Running Cost (INR x 100000)

Hybrid energy based systems, with various combinations of alternative energy sources were analysed using the proposed simulation procedure. To cool 1600 lts of milk per day (Table 1) the cooling capacity of the system should be around 40 kW. The quantity of each energy source available, and the quantity required to meet the cooling needs in a hilly region is shown in Fig. 4. It is observed that the available energy sources are less than the required quantity. So any single source available in this region does not fulfill the required cooling need. Therefore, to meet the total cooling load, all the available energy sources have to be used in suitable combinations.

COPOS

6. Results and discussion

5 0

0.2

0.4

0.6

0.8

1

Ratio of Energy Sources

0 BM

BG

GG

Fig. 4. Available and required quantities of available energy sources for cooling in HR.

Fig. 6. Variations in capital and running cost of the hybrid energy based cooling systems in HR with various combinations.

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BM-BG

6.5

BM-GG

Life Cycle Cost (INR x 10000000)

Payback Period (Years)

7 BG-GG

6

5.5 5 4.5

3.9 BM-BG

3.7

BM-GG

BG-GG

3.5 3.3 3.1 2.9 2.7 2.5

4 0

0.2

0.4

0.6

Ratio of Energy Sources

0.8

0

1

0.2

0.4

0.6

0.8

1

Ratio of Energy Sources

Fig. 7. Payback period of the cooling systems in HR with various combinations.

Fig. 9. LCC variation of hybrid energy based cooling systems in the Hilly Region.

contribution is greater than 80%, the capital cost of the combinations, BM-GG and BG-GG are close to each other (variation is less than 10%). The line representing the capital cost of BM-BG shows a high value than the others. Therefore, the BM-BG combination is not considered in the hilly region. When the gobar gas contribution is 70%, the BM-GG and BG-GG combinations show a low running cost compared to BM-BG combination. Therefore, gobar gas contribution is maintained 60e70% in BM-GG and BG-GG combinations to obtain a low running cost. So the energy combination with gobar gas contribution is very significance to reduce the capital and running cost in the hilly region. Fig. 7 shows that the variation of payback period of hybrid energy based cooling system in hilly region. The combinations BM-GG and BG-GG show a lowest payback period because of its lowest value of running cost, while the gobar gas contribution is maximum. It is observed that the system with 70% gobar gas contribution is appropriate one in the hilly region. If the ratio for energy source is more than 80%, a high payback period has been observed. Moreover the difference in payback period in all the energy combinations are very narrow (less than 10%) when the ratio for energy source is more than 80%. This shows that it is not advisable to maintain the ratio for energy source above 80% in the hilly region. The Figure also shows that the contribution of GG should be 60e70% in BM-GG and BG-GG combinations to obtain the lowest payback period. Fig. 8 shows that the Net Present Value (NPV) of the various combinations of hybrid energy based cooling system in hilly region. The trend shows that the NPV of BM-GG and BG-GG are positive if the contribution of GG is more than 20%. Therefore these

combinations are preferable once in the Hilly Region. The variation of Life Cycle Cost (LCC) with the ratio of energy sources has been analysed and plotted in Fig. 9. The trend of BM-GG and BG-GG combinations shows that the LCC is low for BM-BG combination, when the gobar gas contribution is kept at the maximum. It is observed that the system with the GG contribution of 70% is appropriate one since for this contribution, LCC value is very low. Fig. 10 shows the variations of Annualized Capital Cost (ACC) and Total Annual Cost (TAC) for the various combinations in HR. The curves show that the ACC of BM-GG and BG-GG combinations are lower than that of BM-BG combination. This has been observed when the contribution of gobar gas is kept at the maximum. When the energy ratio is less than 20%, the gobar gas composition is dominating and the ACC of BM-GG and BG-GG combinations are very low and close to each other. Therefore both the combinations can be used at this range. The Total Annual Cost (TAC) is also studied and plotted in Fig. 10, the curves also show a similar trend observed for ACC. Therefore to get the best performance of TAC gobar gas contribution should be kept at the maximum. The Figs. 5e10 show that the BM-GG combination gives the highest COPOS (0.18e0.23) due to the higher heating value and conversion efficiencies of biomass and gobar gas sources and also lower running cost. However this combination has higher capital cost than BM-BG and BG-GG combination, which is due to the cost involved in the installation of biomass plant. Moreover, the payback period, ACC and TAC of BM-GG combination is low and its NPV and LCC are better than the other two combinations. Therefore, the

3.4

3.85

4 3 2 1 0 -1 -2

0

0.2

0.4

0.6

0.8

BM-GG (ACC)

BG-GG (ACC)

BM-BG (TAC)

BM-GG (TAC)

BG-GG (TAC)

3.8

3.3

3.75

3.25

3.7

3.2

3.65

Ratio of Energy Sources 3.6

3.15

-3 -4

1

BM-BG (ACC)

TAC (INR X 100000)

3.35

5 ACC (INR X 100000)

Net Present Value (INR x 100000)

6

BM-BG

BM-GG

BG-GG

0

0.2

0.4 0.6 Ratio of Energy Sources

0.8

1

-5 Fig. 8. NPV of the cooling systems in HR with various combinations.

Fig. 10. ACC & TAC variation of hybrid energy based cooling systems in the Hilly Region.

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Fig. 11. Sensitivity of COPOS to the various input parameters in HR. Fig. 13. Sensitivity of PBP to the various input parameters in HR.

hybrid energy system operating with BM-GG combination is the most appropriate one in the hilly region. The simulation results reveal that the gobar gas contribution has great impact in all the economic value in the hilly regions. Therefore 70% of gobar gas contribution in any combination shall be considered as the suitable combination in the hilly region. 6.1. Sensitivity analysis The sensitivity analysis is performed using standard procedure [51,52] to find the impact of the variation in the relavant parameters on the COPOS, running cost and payback period. The most important parameters considered in this study are cooling load demand, conversion efficiency of the energy sources, capital cost of the energy conversion system, cost of the energy sources, interest rate and life time of the system. These values are usually based on past experience with similar system or with current market values. In hilly region (HR), BM-GG combination with 60:40 energy proportion ratio has been recommended for the best combination. A sensitivity analysis has been carried out for this recommended combination to assess the impact of changes in input parameters. In tornado diagram, the vertical axis lists the factors considered for the sensitivity analysis and the values on the horizontal axis represents the COPOS. The uncertainty in the conversion efficiency of various energy sources and cooling load on the COPOS is shown in Fig. 11. The diagram indicates that the uncertainty in cooling load and conversion efficiencies of both biomass and gobar gas energy sources have the maximum impact on COPOS. The individual variation of conversion efficiency of each energy sources is responsible for a low incidence in the variation range (less than 2%).

Figs. 12 and 13 show the tornado diagram of running cost and payback period for the hybrid energy based cooling system in HR. The effect of varying the cost of each component and the fuel cost of each energy sources in energy conversion process can be seen in Figs. 12 and 13. It is observed that the variation in the interest rate has a significant effect on the running cost and payback period. The variation on the cost of biomass gasifier, gobar gas plant and the cost of energy sources are responsible for a low incidence in the variation range in the running cost and payback period. 7. Conclusion The possibility of combining the renewable energy sources such as biomass, biogas and gobar gas to operate a VARS based milk cooling system in hilly region has been studied. In the hilly region, if the three energy sources (BM, BG and GG) are combined, a VARS can be operated to meet the entire cooling load without the support of conventional energy systems. A system that operates with BM & GG, will be the best combination, since it has an overall COP of 0.214. The proposed system that replaces VCRS by VARS shows the payback period between 4.8 and 6.4 years. This is a reasonable value for the implementation of the proposed hybrid combination. However, if the combination BM-GG is used, the lowest payback period (5 years) could be obtained. Moreover it shows that the energy combination with gobar gas contribution is very significance to reduce the capital cost, running cost and life cycle cost of the system. The NPV trend shows that the BM-GG combination is positive when the gobar gas contribution is up to 85% in the overall blend. So this combination is acceptable one in the hilly terrain. The sensitivity analysis proves that the uncertainty in input parameters such as energy conversion efficiency and interest rate influence the output parameters of the COPOS, capital cost, running cost and payback period. References

Fig. 12. Sensitivity of RC to the various input parameters in HR.

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