CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 57, 2017 

A publication of 

 
The Italian Association 

of Chemical Engineering 
Online at www.aidic.it/cet 

Guest Editors: Sauro Pierucci, Jiří Jaromír Klemeš, Laura Piazza, Serafim Bakalis 

Copyright © 2017, AIDIC Servizi S.r.l. 

ISBN 978-88-95608- 48-8; ISSN 2283-9216 

Energy Saving in Industrial Process Based on the Equivalent 
Production Method to Calculate Energy Performance 

Indicators  
Guillermo E. Valenciab, Yulineth Cardenasa*, Erni S. Ramosb, Alexis Moralesc, 
Juan C. Camposb 
aIndustiral Engineering Program, Universidad del Atlantico, Puerto Colombia – Atlantico, 081001 
bMechanical Engineering Program, Universidad del Atlantico, Puerto Colombia – Atlantico, 081001 
cProcess Engineering Division, Monomeros S.A., Via 40, Barranquilla - Atlantico 
ydcardenas@mail.uniatlantico.edu.co 

This paper presents the estimation and analysis of energy performance indicators based on the equivalent 
production method to improve the decisions and operational actions to reduce the energy consumption of a 
fertilizer company in Colombia, where the global consumption of natural gas in the plant is 4800 kcf per day 
for an equivalent production of 1,029 MT of NPK fertilizer 15-15-15, where the 63.4% of the energy is 
consumed by the complex fertilizers line, the 29.2% by equipment of the energy supply plant, and finally the 
7.4% is consumed by the fertigation SoluNKP plant. Based on the standard ISO 50001 and the operational 
data for 2015, some energy performance indicators such as the baseline and goal line of consumption, the 
actual consumption rate compared to the theoretical consumption index, the efficiency Index Base 100 and 
finally the consumption trend accumulated (CUSUM) were calculated, allowing to identify energy saving 
potentials of 16.1% through good operational practices without technological changes, besides 25.6% for 
production planning. Finally, the natural gas potential savings identified have been achieved by the 
organization through the implementation of an Integrated Energy Management System. 

1. Introduction 

Nowadays, a worldwide environmental crisis is latent with serious consequences in the way that people feed 
and generate power. Thus, encouraging the use of renewable energies and the improvement of energy 
efficiency in industrial processes through the implementation of Energy Management Systems, which allows to 
reduce the energy consumption in 37% of the current worldwide industrial energy consumption (Abdelaziz et 
al., 2011). Moreover, researches conducted by the International Energy Agency (IEA) show evidences that 
approximately the 40% of CO2 emissions, including combustion processes and heat and power generation, 
are related to industrial processes (Sucic et al., 2015). According to the previously stated, the implementation 
of Energy Management Systems turns out into an orientation for industrial companies to assemble efficient 
productive structures, thus a better way to the use of energy resources, which allows to increase the industrial 
competitiveness so that to use it as a way to encourage the innovation, at the same time these systems blend 
with facts such as environmental sustainability and industrial eco efficiency (May et al., 2016). 
The performance of the equipments, is one of the main factors which encourage industrial competitiveness, 
considering this as one of the main actives in the production chain. The measurement and quantification of 
energy efficiency in equipment, processes and factories is the first step to energy management in any 
company. Energy management requires information related to the energy consumption and production 
through the time in order to calculate energy performance indicators that evidence the actual energetic and 
productive state of industrial processes (Campos et al., 2007; Campos and Lora, 2009; Campos and Prias, 
2013). 
Energy efficiency is one of the most promising tools in the race to reduce the energy consumption, thus the 
energy costs (Schulze et al., 2016), therefore companies with high energy consumption such as paper, 

                               
 
 

 

 
   

                                                  
DOI: 10.3303/CET1757119

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Please cite this article as: Valencia-Ochoa G., Cardenas Y., Ramos E., Morales A., Campo J., 2017, Energy saving in industrial process based 
on the equivalent production method to calculate energy performance indicators, Chemical Engineering Transactions, 57, 709-714  
DOI: 10.3303/CET1757119 

709



petrochemical, metallurgy and so forth and so on, have achieved continuous and successful progress with 
respect to energy efficiency management within the last three decades (Indicators, n.d.) (ENERGY, 2007). 
Nowadays, energy efficiency is measured with some evaluation methods such as e-KPI method implemented 
in industrial processes, which presents as a way of evaluation seven steps that conduct to the calculation of 
performance indicators related to the energy consumption and productivity (May et al., 2015), which allows to 
translate the cause – effect relations, thus supporting operative decisions in the company. Other energy 
performance evaluation methods are implemented in non-residential buildings where the methodology gathers 
five relevant categories: engineering calculation, simulation, statistical methods, automatic learning and other 
methods, based on an exhaustive analysis so that to classify and evaluate the energy performance in non-
residential buildings (Borgstein et al., 2016). 
This paper aims the application or equivalent production in order to obtain energy performance indicators for a 
petrochemical plant located in Colombia, with the purpose to reduce the energy consumption following stages 
of strategic decisions and energetic characterization, which represent fundamental for the proper 
implementation of and Energy Management System. This work presents results of an energy diagnosis 
through the evaluation of energy indicators based on historical information of energy consumption and 
productivity, thus identifying opportunities of organizational, energetic and technological upgrades for the 
company so that to address the managing department of the company in the creation of an organizational 
structure and adoption of undertaken commitments to conduct to the effective implementation of an Energy 
Management System. 

2. Methodology 

This work shows a description of the power generation system of the plant and each stage of the fertilizer 
production chain, furthermore, it is described the scope of an energy management system developed in the 
industrial complex so that to identify the energy saving potentials. Finally, the equivalent production method is 
presented through the use of fundamentals of mathematics, applied to the energetic and productive 
characterization of the fertilizer plant, the main source of energy is natural gas, which is directly related to the 
production of fertilizers. The equivalent production method allowed to estimate the energy performance 
indicators of the plant, in addition to identify energy and economic saving potentials, in order to look for saving 
potentials project without technological changes. 

2.1 Industrial Process and Power Generation System 

The agronomic complex produces a wide variety of fertilizers with different components and different blending 
processes using as raw material: phosphate rock, ammonia, nitric acid, potassium sulphate or potassium 
chloride, ammonia phosphate, and ammonia sulphate as a product. The fertilizer production complex is 
divided in humid and dry zone. The humid zone is integrated by the stages of dissolution, where phosphate 
rock enters in reaction with the nitric acid, thus obtaining a solution rich in phosphoric acid and calcium nitrate, 
followed by a deposition stage, where the product reacts with an ammonia sulphate solution, ammonia nitrate 
and ammonia phosphate formation and a deposition of calcium sulphate, afterwards, during the filtration, the 
calcium sulphate solution is separated in order to stabilize the pH and nitrogen/phosphor ratio, subsequently 
the product goes through a boiling process until obtaining concentrated salts with 5 – 10% of humidity.  
In the other hand, the dry zone is integrated by granulation stage where the salts make contact with a solid 
phase composed by phosphate salts and potassium, so that to obtain fertilizer grains, subsequently the 
product is dried with hot air until the moisture is reduced to 1.0%, afterward it goes through a sifting process 
which allows to get three different streams of the same product: a thick grain stream, a fine grain stream and 
the stream with the proper size of grain, it means the size of grain required by the customer. After that, the 
stream of thick grain goes through a breaking process so that to reduce its size and together with the fine 
grain stream is recycle for the granulation stage. Finally, the final stream is sent to the cooling stage until 
obtain a fertilizer with the proper handling temperature. 
The required power of the complex to carry out the previously described processes is generated by two gas 
turbines with a net capacity of 6.9 MW, the power generation process starts with the air compression from 
atmospheric pressure to 186 psig and temperature of 385 ºC followed by the blending with natural gas and 
start the combustion in the combustion chamber of the turbine, the heat gases flow are expanded in the 
turbine which rotates at 14000 rpm, this rotational energy is transferred through central shaft to a speed 
reductor until 1800 rpm and finally transmitted to a power generator of 6600 V at a frequency of 60 Hz. At the 
exit of the gas turbines, the heat waste products have a temperature of 550 – 560 ºC which are seized in the 
boiling recovery attached to the gas turbines, these devices generate saturated vapor at 18kg/cm 2 which is 
transported to the fertilizers plant and other facilities of the complex. The exhaust gases are sent to the 
environment at a temperature of 237ºC. 

710



2.2 Energy Management Systems 

The model for an energy management system is integrated by three fundamental stages that allows to 
improve the energy consumption of the company and reduce energy consumption without the levels of 
production. The first stage is the strategic decision where is necessary a high level commitment of the senior 
management of the company in order to assign the resources available for the Energy Management System, 
the starting point is the energetic characterization of the plant, followed by a socialization of the results with 
the senior management, subsequently the whole structure of the company is aligned toward the rational use of 
energy, and finally the structure is upgraded and validated according to the current processes. 
The second stage is the calculation and set up of energy performance indicators and the identification of 
significant controlled variables within the main areas of the company, afterward to identify corrective plan, 
control of events, operative procedures, in addition to inner projects with energy saving potentials. A 
monitoring system is established in the system, accompanied of an energy diagnosis, improvement 
opportunities identification, and so forth and so on. 
Finally, in the operative stage, it is necessary to constantly track and socialize energy performance indicators, 
moreover the evaluation of proper manufacturing practices, maintenance, production, and coordination 
obtained through the implementation of projects encouraged to the energy efficiency management. 

2.3 Equivalent Production Method 

This method is based on the calculation of an energy base line with the linear form as in Eq(1). 

𝑦 = 𝑚𝑥 + 𝑏 (1) 

Obtained from the linear regression of historical data of energy consumption and production. As a case study 
for a petrochemical company located in Colombia dedicated to the production and commercialization of 
fertilizers in which is highlighted the series NPK 15-15-15. This linear regression identifies two variables that 
represent the energetic behavior of the company in one hand there is the energy intensity represented with 
the letter “m” and is given by the slope the linear regression, this variable indicates the energy consumption 
directly related to the level of production, on the other hand it is found the variable “Eo” which represents the 

energy consumption non related to the production, therefore it is presented a model to identify the variables 
which directly affects the energy consumption (Velázquez et al., 2013). In order to calculate an equivalent 
production, it is necessary to determine a value for the energy consumption as the sum of every level of 
production times its corresponding energy intensity for every different product, as in Eq(2). 

𝐶𝐸 = 𝛽0 + 𝛽1 𝑃1 + 𝛽2𝑃2 + ⋯ + 𝛽𝑗 𝑃𝑗 (2) 

The variable “Pj” represents the amount of units produced for every different product considering the model of 
production, the coefficients “βj” correspond to the energy intensity for every kind of product, and “βo” defines 
the energy consumption non related to the production. Therefore, the energy intensity is calculated as in 
Eq.(3). 

𝛽𝑗 =
𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 

𝑈𝑛𝑖𝑑 𝑜𝑓 𝑃𝑟𝑜𝑑𝑢𝑐𝑡 𝑗
 (3) 

Once calculated the coefficients for energy intensity, the intensive products related to the energy consumption 
are identified, as equal as the production levels, thus indicating the process with higher rates of energy 
consumption as shown in Eq(4). 

𝛼𝑖 =
𝛽𝑖

𝛽𝐵𝑎𝑠𝑒
=

𝑈𝑛𝑖𝑑𝑠 𝑜𝑓 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑗

𝑈𝑛𝑖𝑑 𝑜𝑓 𝑏𝑎𝑠𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡
 (4) 

The energy relationship of the products αj, corresponds to the number of units of product base that can be 
elaborated with the energy used to produce a unit of product (j). With this information, a production according 
to energy equivalencies αj is set, besides the levels of production for product j as shown in Eq(5). 
 

𝑃𝑒𝑞 = 𝑃𝐵𝑎𝑠𝑒 + 𝛼1𝑃1 + 𝛼2𝑃2 + ⋯ + 𝛼𝑗 𝑃𝑗 (5) 

3. Results 

The analysis tools used for the energy characterization of the plant were the production and energy 
consumption analysis through the time. In addition, some energy performance indicators such as the base line 
and goal line and actual index of consumption compared with the theoretical index of consumption in order to 
identify energy saving potentials by good practices of production and good planning of the production 

711



respectively. Within the energy performance indicators, it is included a control indicator known as the base 
100 index of efficiency. Prior to the analysis of indicators of performance is makes necessary the application of 
limits of control for data of consumption of gas and production so that to exclude data considered atypical for 
the set of data of shows in the characterization. 
According to the data supplied by the team of energy managers, and after applying the first filter in the charts 
of boundary control, shown in Figure 2, it is obtained three different base lines, as shown in Figure 1, for each 
fertilizer, with a correlation coefficient of 0,49618, 0,82515 and 0,64084 for the references 15-15- 15, 13-26-6, 
and 17-6-18-2 respectively. 
 

 
Figure 1. Base lines for energy consumption for three different produced fertilizers. 

The Figure 2 shows the graphics of boundary control, which set an upper limit and a lower limit separated with 
three times the standard deviation of the average Value, where is observes that four (4) data of production are 
below the limit lower of production, while a (1) data is above the limit of consumption top which means that 
these data considered as outliers will not be considered for the productive plant energy analysis, while for 
energy consumption, there are five (5) data that are considered outliers. 

  
Figure 2. Boundary control charts a) Energy Consumption, b) Equivalent production of fertilizers. 

 
The index of efficiency base 100 relates the actual and theoretical consumption, this indicator generates alerts 
about positive or negative variations in the energy efficiency of the process, thus facilitating the analysis and 
proposed plans of action on the basis of energy improvements, allowing the analytical interaction between 
production and energy consumption, pointing to a better energy performance of the fertilizer plant processes. 
As is seen in the Figure 5a, to express two intervals of results B100 < 100% and B100 ≥ 100%. For the case 
when the index is greater than 100% translates into a good energy performance, since the real power 

E = 10,654 P + 14859 
R² = 0,49618 

E = 12,093 P + 10781 
R² = 0,82515 

E = 17,31 P + 14049 
R² = 0,64084 

11000

14000

17000

20000

23000

26000

29000

100 300 500 700 900 1.100 1.300 1.500 1.700

E
n

e
rg

y
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k
W

h
/d

a
y

) 

Production (TM) 

Reference 15-15-15 Reference 13-26-6 Reference 17-6-18-2

Lineare (Reference 15-15-15) Lineare (Reference 13-26-6) Lineare (Reference 17-6-18-2)

5000

15000

25000

35000

45000

dic-14 feb-15 abr-15 may-15 jul-15 sep-15 oct-15 dic-15

E
n

e
rg

y
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k
W

h
/d

a
y

) 

Date 

Mean Energy Energy Upper Limit
Energy Lower Limit Energy

0

500

1000

1500

2000

2500

dic-14 feb-15 abr-15 may-15 jul-15 sep-15 oct-15 dic-15

P
ro

d
u

ct
io

n
 (

T
/d

a
y

) 
 

Date 

Mean Production Production Upper Limit
Production Lower Limit Produccion

B A 
F
i
g
u
r
e
 
2
. 
G
r
a
fi
c
a
s 
d
e
 
c
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712



consumption was less than the theoretical power consumption, therefore in Figure 5a points above the limit of 
100% are considered good energy performance data located in the area of energy efficiency of the plant. On 
the other hand, when the index of efficiency is lower to 100%, is indicates that the data belong to a zone of 
inefficiency energy of the plant. However, for the analysis of the fertilizer plant, in the area of efficiency energy, 
several peaks of high efficiency with a random behavior are evidences, by what it indicates that these peaks 
located in the area of efficiency energy not are result of improvements in the energy management system of 
the company. 

  
Figure 3. Energy Performance Indicators for the fertilizer plant. a) Index of base 100 efficiency, b) Index of 

energy consumption. 

Comparison of actual and theoretical consumption index is observed in Figure 5b, where data in blue 
represent the rate of theoretical consumption, while the red points represents the actual consumption. It 
evidenced that the rate of actual consumption varies in 120 and 20 kWh/Mt of fertilizer, indicating that the 
company has production levels above the critical equivalent production directly related to the technology of the 
plant, which is calculated as 1020 TM according to the theoretical consumption index, clearly the company 
has much higher production levels, that indicate a better performance energy given the low rates of 
consumption. Starting from this, it reflects that the company has a very good planning with regard to their daily 
production represented in the historical data supplied for 2015. 

4. Conclusions  

Taking into account the successful results of energy diagnosis in the plant, it was considered the 
implementation of an energy management system according to the ISO standard 50.001 in the petrochemical 
company in Colombia attacking to significant uses of energy in the plant, it is necessary to provide continuity 
to the stage of implementation of the system, in which occurs the monitoring and control of energy indicators, 
the accompaniment in the verification of the functioning of the operational control system and the 
implementation of technological improvements of void, or low investment.  
In order to guarantee the improvement of the use of energy and the sustainability of the reduction of energy 
for the company with low investment measures, it is necessary to develop a Software for tracking, 
measurement, and analysis of the energy performance for each significant use of energy installed and set in 
operation, so that to calculate the equivalent production of the different types of produced fertilizers in the 
plant. 
Finally, it is necessary a third stage of monitoring and adjustment in which is performed a measurement of 
results, to identify the technological improvements of medium and high investment, to evaluate the energy 
savings potentials obtained with the implementation of the system, to document the energy management 
system, and to incorporates to the management system of the company, furthermore to perform the exercise 
of audit external for purposes of ISO 50001 standard certification. 

References 

Abdelaziz, E.A., Saidur, R., Mekhilef, S., 2011. A review on energy saving strategies in industrial sector. 
Renewable and Sustainable Energy Reviews 15, 150–168. doi:10.1016/j.rser.2010.09.003 

Borgstein, E.H., Lamberts, R., Hensen, J.L.M., 2016. Evaluating energy performance in non-domestic 
buildings : A review. Energy & Buildings 128, 734–755. doi:10.1016/j.enbuild.2016.07.018 

174% 

78% 78% 

60%

80%

100%

120%

140%

160%

180%

0 50 100 150 200 250

 E
ff

ic
ie

n
cy

 I
n

d
e

x
 B

a
se

 1
0

0
 

Days 

A) 

0

20

40

60

80

100

120

140

-400 100 600 1100 1600
C

o
n

su
m

p
ti

o
n

 I
n

d
ic

e
 (

K
W

h
/T

M
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Equivalent Producción (TM) 

IC Theoretical

IC Actual

B) 

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Campos, J.C., Lora, E.D., 2009. Manual de mantenimiento centrado en la eficiencia energética para sistemas 
industriales. Universidad del Atlantico, Barranquilla. 

Campos, J.C., Meriño, L., Tovar, I.R., Prias, O., Quispe, E.C., Vidal, J.R., Ulianov, Y., Castrillon, R., Lora, 
E.D., 2007. Sistema de Gestion Integral de la Energia. Universidad del Atlantico, Barranquilla. 

Campos, J.C., Prias, O., 2013. Implementación de un Sistema de Gestión de la Energía; Guía con base en la 
norma ISO 50001. Universidad Nacional de Colombia, Bogota, Colombia. 

Indicators, E., n.d. Tracking Industrial Energy Efficiency and CO 2 Emissions ENERGY. 
May, G., Barletta, I., Stahl, B., Taisch, M., 2015. Energy management in production : A novel method to 

develop key performance indicators for improving energy efficiency 149, 46–61. 
doi:10.1016/j.apenergy.2015.03.065 

May, G., Stahl, B., Taisch, M., 2016. Energy management in manufacturing: Toward eco-factories of the future 
- A focus group study. Applied Energy 164, 628–638. doi:10.1016/j.apenergy.2015.11.044 

Schulze, M., Nehler, H., Ottosson, M., Thollander, P., 2016. Energy management in industry e a systematic 
review of previous fi ndings and an integrative conceptual framework. Journal of Cleaner Production 112, 
3692–3708. doi:10.1016/j.jclepro.2015.06.060 

Sucic, B., Al-Mansour, F., Pusnik, M., Vuk, T., 2015. Context sensitive production planning and energy 
management approach in energy intensive industries. Energy 108, 1–11. 
doi:10.1016/j.energy.2015.10.129 

Velázquez, D., González-Falcón, R., Pérez-Lombard, L., Marina Gallego, L., Monedero, I., Biscarri, F., 2013. 
Development of an energy management system for a naphtha reforming plant: A data mining approach. 
Energy Conversion and Management 67, 217–225. doi:10.1016/j.enconman.2012.11.016 

 

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