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A model of energy management analysis, case study of a sugar factory in Turkey

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Abstract

This study presents a case study of energy management in a sugar factory in Turkey. The main idea of the study is to analyse energy consumption, the quantity of material production, and figure out a suitable energy efficiency for the case study of a sugar factory subsequently. Firstly, a material production and energy consumption audit were performed for the sugar factory. Secondly, energy efficiency was calculated from the energy data. The SPSS (Statistical Package for the Social Sciences) statistical software was used to ensure the accuracy of the data. The factory’s energy consumption was calculated as 43,590.25 toe (tons of oil equivalent) over the last year. These results were used for CUSUM (Cumulative Sum Deviation Method) graphics. This research poses the consumption of energy, cost of energy and the relationship between energy usage and material production of sugar. The unit of energy cost was 688.22 [$/toe] for the last year. This result showed that the factory decreased the unit of energy by optimisation. The results indicated that the investigated sugar factory should pay attention to the energy management issue in order to comply with the Energy Efficiency of Turkish Law and Directives.

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Abbreviations

\( {\dot{{\text{C}}}}_{\text{En}} \) :

the unit of energy cost, $/toe

\( {\text{E}}_{\text{e}} \) :

total energy consumption, toe

a:

slide in the horizontal axis

b:

slope of the line in the horizontal axis

\( {\text{C}}_{\text{cost}} \) :

total investment cost, $

\( {\text{CS}}_{\text{i}} \) :

sum of CUSUM value

\( {\text{D}}_{\text{i}} \) :

difference value

E:

energy consumption, Gcal; toe

\( {\text{E}}_{\text{j}} \) :

consumption of energy amount, toe

\( {\text{E}}_{\text{p}} \) :

total energy production, toe

i, j:

notation

P:

material production, tonnes

\( {\text{P}}_{\text{i}} \) :

specific variable of material production amounts, tonnes

\( {\text{P}}_{\text{pr}} \) :

total sale price, $

\( {\text{R}}^{ 2} \) :

R Squared (Linear regression analysis symbol)

t:

tonnes

ANOVA:

analysis of variance

CUSUM:

cumulative sum

CUSUMSQ:

cumulative sum of squares

DE:

differential evolution

GA:

genetic algorithm

HVAC:

heating, ventilating and air conditioning

PASW:

predictive analytics software

PDS:

public distribution system

PSO:

particle swarm optimization

SEC:

specific energy consumptions, \( {\text{toe/t}} \)

SPSS:

statistical package for the social sciences

Σ:

Sum

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Acknowledgement

This study was supported by a Scientific Research (Date of work: February 2010 to January 2013) for the case of a sugar factory in Turkey. It was carried out in Çumra Sugar Integrated Plant. The energy data were taken with permission from the factory administration having in collaboration with the Department of Factory Central Monitoring and Directorate of Maintenance and Energy.

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Taner, T., Sivrioğlu, M., Topal, H. et al. A model of energy management analysis, case study of a sugar factory in Turkey. Sādhanā 43, 42 (2018). https://doi.org/10.1007/s12046-018-0793-2

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  • DOI: https://doi.org/10.1007/s12046-018-0793-2

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