Analysis of fish refrigeration electricity consumption

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International Scientific Conference “Environmental and Climate Technologies”, CONECT 2018 International Scientific Conference “Environmental and Climate Technologies”, CONECT 2018

Analysis ofInternational fish refrigeration electricity consumption The 15thof Symposium on District Heating and Cooling Analysis fish refrigeration electricity consumption

Edvins Terehovics*, Raimonda Soloha, Ivars Veidenbergs, Dagnija Blumberga Assessing the feasibility of using the heat demand-outdoor Edvins Terehovics*, Raimonda Soloha, Ivars Veidenbergs, Dagnija Blumberga Institute of Energy Systems and Environment, Riga Technical University, Azenes iela 12/1, Riga, LV-1048, Latvia

temperature function for a long-term district heat demand forecast Institute of Energy Systems and Environment, Riga Technical University, Azenes iela 12/1, Riga, LV-1048, Latvia a,b,c

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*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre Abstract I. Andrić Abstract a IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal The non-energy-intensive nature of the food processing industry has led to a common trend where management energy has only b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France secondary role costs, resulting in minimal from management and short-term solution. Within cold c to other productions The non-energy-intensive nature the food processing industry has Atlantique, led to a common trend where management energy has only Département SystèmesofÉnergétiques et Environnement -oversight IMT 4 rue Alfred Kastler, 44300 Nantes, France storage facilities, 60–70productions % of the electrical energyinused is foroversight refrigeration. For fish processing companies, one of the main secondary role to other costs, resulting minimal from management and short-term solution. Within cold energy users are the refrigeration The energy aim of the is to make algorithm based on case study order to storage facilities, 60–70 % of theunits. electrical usedcurrent is for paper refrigeration. For an fish processing companies, one ofinthe main evaluateusers fish refrigeration electricity consumption compare studies. energy are the refrigeration units. The aim and of the currentresults paper with is tosimilar make an algorithm based on case study in order to Energy consumption forelectricity processing fish depends on installation, and process. Process of cooling and evaluate fish refrigeration consumption and compare results withequipment similar studies. Abstract refrigeration builds up about 16 % of thefish total depends energy in on canning sector. This study hasand shown that refrigeration up about Energy consumption for processing installation, equipment process. Process ofbuilds cooling and 24 % in heating average. From calculations, it total can be concluded that sector. average electricity consumption for fish refrigeration the refrigeration builds up about 16 commonly % of the energy in the canning study shown that refrigeration up at about District networks are addressed in literature asThis one of thehas most effective solutions forbuilds decreasing the factory kWh per toncalculations, of product. In sources can be found electricity that consumption industrial freezers are 24 % inis 380 average. From it literature, can sector. be concluded that average consumption fish refrigeration at heat the greenhouse gas emissions from the building These it systems require highelectricity investments which for arefor returned through the 70–130 kWh per tonper of ton product. factory 380to kWh of climate product.conditions In literature, sources it can be found that electricity for future industrial freezers are sales. is Due the changed and building renovation policies, heat consumption demand in the could decrease, 70–130 kWhthe perinvestment ton of product. prolonging return period. ©The 2018 Thescope Authors. Published main of this paper isby to Elsevier assess theLtd. feasibility of using the heat demand – outdoor temperature function for heat demand © 2018 The Authors. by Ltd. This is an open accessPublished article under thelocated CC BY-NC-ND (https://creativecommons.org/licenses/by-nc-nd/4.0/ © 2018 The Authors. Published by Elsevier Elsevier Ltd. forecast. The district of Alvalade, in Lisbon license (Portugal), was used as a case study. The district is consisted) of 665 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review responsibility of typology. the scientific committee of the (low, International Scientific Conference ) district This is an open access article under the CC period BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/ buildings that vary in both construction and Three scenarios medium, high) and three Selection and peer-review under responsibility of the scientific committeeweather of the International Scientific Conference ‘Environmental ‘Environmental and Climate Technologies’, CONECT 2018. Selection and peer-review under responsibility of the scientific committee of the International Scientific Conference renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were and Climate Technologies’, CONECT 2018. ‘Environmental Climate 2018. previously developed and validated by the authors. compared with and results from Technologies’, a dynamic heat CONECT demand model, Keywords: refrigeration; COP; fish canning; energychange efficiency The results showed that when only weather is considered, the margin of error could be acceptable for some applications Keywords: COP; fishwas canning; (the errorrefrigeration; in annual demand lowerenergy than efficiency 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Cooling.

E-mail address:author. [email protected] * Corresponding E-mail address: [email protected] Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 1876-6102 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection under responsibility of the scientific of the International Scientific Conference ‘Environmental and Climate This is an and openpeer-review access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) Technologies’, CONECT 2018. Selection and peer-review under responsibility of the scientific committee of the International Scientific Conference ‘Environmental and Climate 1876-6102 © 2017 The Authors. Technologies’, CONECT 2018. Published by Elsevier Ltd. 1876-6102  2018 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of the International Scientific Conference ‘Environmental and Climate Technologies’, CONECT 2018. 10.1016/j.egypro.2018.07.084

Edvins Terehovics et al. / Energy Procedia 147 (2018) 649–653 Author name / Energy Procedia 00 (2018) 000–000

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1. Introduction The large amount of the food processing industry shows potential for energy savings. The non-energy-intensive nature of the food processing industry has led to a common trend where energy management has only secondary role to other productions costs, resulting in minimal oversight from management and short-term solution [1]. Overall figures show that cold storage facilities use 60–70 % of the electrical energy for refrigeration purposes. Therefore cold store users have incentive to reduce electricity consumption for refrigeration [2–4]. One of the main reasons for such large electricity consumption is the poor thermal insulation of freezers, the freezer door is not hermetically sealed and other factors. Some of these shortcomings can be prevented, and it would immediately reduce electricity consumption by 20 % [3, 5]. For fish processing companies, one of the main energy users are the refrigeration units, which divided by compressor type and freezing cycle. Compressors divided into the following groups: rotary type compressors, piston compressors centrifugal compressors. The refrigeration cycles divided into gas and steam cycles. In gas cycles, air is used as a refrigerant, but different freons (CF3Cl, CF2CL2, etc.), carbon dioxide, ammonia NH3 are used in the steam cycle. Refrigeration unit energy efficiency is related to technological solutions, operating conditions of the technology and the desired refrigeration temperatures, pressure and other considerations [6–8]. Basic compression cycle for freezer consists of four main stages (see Fig. 1). In the first stage, the refrigerant (for example, ammonia) is compressed in the compressor, during it the temperature and pressure of the refrigerant increases [6–8]. Q1 Cond 2

Cond 1 Condenser

Expansion device

Comp2

Exp1

W

Compressor

Exp2 Evaporator Evap1

Comp1

P1 T1 t1 High pressure/ temperature side Low pressure/ temperature side

Evap2

P2 T2 t2

Q2 Cold soace Fig. 1. Principal scheme of a vapor compression cycle [6–8].

In the second stage, the refrigerant enters into a condenser, the refrigerant changes its gaseous state to liquid through cooling. In practice, coolers are cooled with water or air [6–8]. In the third stage, the cooled refrigerant goes through throttle valve where refrigerant temperature and pressure decreases. In the fourth stage, the refrigerant fed to the evaporator. In the evaporator, refrigerant exchanger through the heat exchanger absorbs the heat of the cold storage, which causes the refrigerant to change the state from liquid to gaseous. The efficiency of refrigeration system is measured using coefficient of performance or COP [6–8]. A specific company was selected in Latvia, which produces canned fish. Company's basic production scheme shown in Fig. 2.



Edvins Terehovics et al. / Energy Procedia 147 (2018) 649–653 Author name / Energy Procedia 00 (2018) 000–000 Fish reception

Fish freezing

Pre-treatment of fish (defrosting, slicing)

Fish processing

Product packing in cans

Sterilization

651 3

Packing cans in boxes

Fig. 2. Basic production scheme of canned fish.

Fish processing in the company is organized in 7 stages. During the first stage, fishes are taken from fishermen or purchased. During the second stage delivered fishes are frozen or stored in a freezer until the start of treatment. During the third stage, fishes are defrosted and cut to be heat-treated at a later stage. During the fourth stage, fishes are baked or smoked. During the fifth stage, baked or smoked fishes are packed in cans, with the addition of sauce or oil. During the sixth stage, the cans are heat-treated with steam and then cooled down. During the seventh stage, cans are packed in boxes and then sent to traders. 2. Methodology In order to understand the possibilities for increasing the efficiency of fish refrigeration, the analysis of Latvian fish processing company was started; the aim of the analysis is to establish specific energy consumption and compare it with similar studies. The algorithm of the fish refrigeration electricity consumption analysis is depicted into Fig. 3.

Fish refrigeration data

Calculation of specific electricity consumption for fish freezing

Data analysis

Proposals for improvements

End of data analysis

Fig. 3. Algorithm of the fish refrigeration electricity consumption analysis.

The algorithm consists of 4 blocks. In the first block, data of the technical and operational parameters of the refrigeration unit are collected. In the second block, based on the previously collected data, calculations of the specific electricity consumption for the fish refrigeration unit are made. In the third block, data analysis and comparison with other fish processing companies is performed. The last block offers proposals for reducing electricity consumption of fish refrigeration. 3. Results Analysis of fish refrigeration electricity consumption was performed on the basis of data got from fish canning company in Latvia.

Edvins Terehovics et al. / Energy Procedia 147 (2018) 649–653 Author name / Energy Procedia 00 (2018) 000–000 Electricity consumption in 2017, MWh

652 4 250 200 150 100 50 0

Freezers

In other factory sites

Fig. 4. Electricity consumption in fish canning factory.

The figure shows data of 2017 electricity consumption in the Latvian fish processing company. The largest electricity consumption is from February to May and from August to December. From the data presented in the graph, it can be concluded that electricity from freezers forms significant part of total electricity consumption. Energy consumption for processing fish depends on installation, equipment and process. Process of heating uses approximately 29 % of the total energy in the canning sector and process of cooling and refrigeration builds up about 16 % [9]. In our case, refrigeration builds up about 24 % in average.

Specific electricity consumption in 2017, MWhel/tfreezed

2,50 2,00 1,50 y = –0.486ln(x) + 2.8125 R2 = 0.8701

1,00 0,50 0,00 0,00

50,00

100,00 150,00 200,00 Frozen fish, tfreezed/month

250,00

300,00

Fig. 5. Specific electricity consumption for fish refrigeration.

Fig. 5 shows data on the specific energy consumption of frozen fish ton per month. From the data, it can be concluded that the specific electricity consumption decreases with the increase in the amount of frozen fish. This correlation is also confirmed by the regression analysis coefficient R2, the value of which is 0.87. The average electricity consumption for fish refrigeration at the factory is 380 kWh per ton of product. In literature sources it can be found that electricity consumption for industrial freezers are 70–130 kWh per ton of product [2, 10]. Some measures that can be implemented to reduce fish refrigeration energy consumption:  Reducing the condensation temperature can increase COP and reduce power consumption. This can be achieved by installing an appropriate heat exchanger in order to achieve sufficiently low condensation temperature also during summer months. Low condensation temperatures can also be ensured if the heat exchanger in the condenser is kept clean and the old ones are replaced by new ones [9];



Edvins Terehovics et al. / Energy Procedia 147 (2018) 649–653 Author name / Energy Procedia 00 (2018) 000–000

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 In case of increasing the refrigerant evaporation temperature in the evaporator by 1 °C, the COP increases by 4 %, but the refrigeration capacity increases by 6 % [9];  The food industry often encounters the fact that the freezer is occasionally present due to the lack of freezing products. During these periods of inactivity, it is necessary to maintain sufficiently low temperatures so that, in the event of supply, the products can be quickly frozen. This can be done by running evaporator fan at low speed using frequency converters. Frequency converters make it possible to reduce fan power without reducing their efficiency. In literature sources it can be found that 1 kWe reduction of fan power can save 1.4–1.6 kWe electricity [9]. 4. Conclusions In order to understand the possibilities for increasing the efficiency of fish refrigeration, the analysis of fish processing company in Latvia was started; the aim of the analysis is to establish specific energy consumption and compare it with similar studies. Energy consumption for processing fish depends on installation, equipment and process. Process of heating uses approximately 29 % of the total energy in the canning sector and process of cooling and refrigeration builds up about 16 %. In our study, refrigeration builds up about 24 % in average. From the results, it can be concluded that the specific electricity consumption decreases with the increase in the amount of frozen fish. The average electricity consumption for fish refrigeration at the factory is 380 kWh per ton of product. In literature sources, it can be found that electricity consumption for industrial freezers is 70–130 kWh per ton of product. References [1]

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