Microsoft Word - PRES22_0064.docx


 
 
 
 
 
 
 
 
 
 
                                                                                                                                                                 DOI: 10.3303/CET2294107 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Paper Received: 06  May  2022; Revised: 16  May  2022; Accepted: 21  May  2022 
Please cite this article as: Wahab A.S.A., Liew P.Y., Rozali N.E.M., Wan Alwi S.R., Klemeš J.J., 2022, Spatial Total Site Heat Integration 
Targeting Using Cascade Pinch Analysis, Chemical Engineering Transactions, 94, 643-648  DOI:10.3303/CET2294107 
  

 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 94, 2022 

A publication of 

 
The Italian Association 

of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Petar S. Varbanov, Yee Van Fan, Jiří J. Klemeš, Sandro Nižetić 
Copyright © 2022, AIDIC Servizi S.r.l. 
ISBN 978-88-95608-93-8; ISSN 2283-9216 

Spatial Total Site Heat Integration Targeting using Cascade 
Pinch Analysis 

Abdul Syakir Abdul Wahaba, Peng Yen Liew*,a, Nor Erniza Mohammad Rozalib, 
Sharifah Rafidah Wan Alwic, Jiří Jaromír Klemešd  
a Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 
Kuala Lumpur, WP Kuala Lumpur, Malaysia  
bDepartment of Chemical Engineering, Universiti Teknologi PETRONAS, 32610, Bandar Seri Iskandar, Perak, Malaysia  
cSchool of Chemical and Energy Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Block N29, 106-02, 
81310 UTM, Johor Bahru, Johor, Malaysia 
dSustainable Process Integration Laboratory – SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of 
Technology - VUT Brno, Technická 2896/2, 616 69, Brno, Czech Republic 
 pyliew@utm.my 

Increasing population growth and rapid industrial development have become the main factors for increasing 
energy consumption. The increase in energy consumption increases the greenhouse gases released into the 
environment. The development of high energy efficiency equipment and energy optimisation tools and 
methodologies have been introduced to tackle the problem of harvesting renewable energy. Total Site Heat 
Integration (TSHI) is one of the energy optimisation methodologies applied in the industrial sector for site-wide 
function, which has proven to reduce energy consumption by analysing the result. The TSHI keeps being used 
by researchers to improve heat energy optimisation across individual processes until it covers the Locally 
Integrated Energy Sectors (LIES) concept. In this research, the TSHI targeting methodology is extended to 
consider the logistic of the process plants, known as the Spatial Utility Problem Table Algorithm (SUPTA). 
Steam headers are flowing in one direction. The plant location affects the entry point of steam generation and 
exit points of the steam consuming process. Steam generated from the downstream of the headers would 
need an additional reverse flow pipeline for sending it to the other plant located upstream of the pipeline. The 
energy cascade is done based on the spatial location, from the utility plant to the farthest process plant in the 
system. This spatial TSHI targeting methodology could be used for simultaneous targeting and design of site 
utility distribution system, which is beneficial for considering heat loss and pressure drop. A case study shows 
that the conventional TSHI and the novel SUPTA methodologies produce the same energy targetting result. 
However, it is shown that reverse flow pipelines increase threefold when the location of the utility plant 
change. 

1. Introduction 
United Nations' Sustainable Development Goals (SDGs) have been proposed as a mutual target between 
countries for ensuring sustainability on the mother earth. SDG 7 is targeted for doubling the improvement rate 
on energy efficiency for energy savings. Process Integration for the industrial process has been progressing 
for resources conservation, such as thermal energy, power, water, chemicals, hydrogen and carbon dioxide. 
Pinch analysis is a well-established methodology for process integration (Klemeš et al., 2018). Total Site Heat 
Integration (TSHI) is an extended Pinch Analysis methodology proposed for energy recovery across multiple 
process plants through a centralised utility system (Liew et al., 2017).  
The method can be used to study energy conservation efficiently on an industrial symbiosis or eco-industrial 
park problem. Energy recovery opportunities could be found in a more extensive system boundary. Butturi et 
al. (2019) reviewed energy recovery potentials for industrial symbiosis in eco-industrial parks and urban-
industrial symbiosis. Boldyryev et al. (2021) presented a design framework for Total Site energy recovery, 
which optimised the heat transfer area and capital cost for the heat exchanger network. Kröhling et al. (2022) 

643



recently proposed using a peer-to-peer automated negotiation mechanism to manage the peer exchange of 
utility to meet their generation and consumption in the eco-industrial parks. 
The plant's location in the Total Site boundary is essential (Chew et al., 2013). The pressure drop and energy 
loss could happen with the steam headers, although the piping system is well insulated and has steam traps. 
Liew et al. (2014b) proposed an extension of the TSHI targeting methodology for incorporating the pressure 
drop and heat loss during the site locations, aided by the Total Site Utility Distribution (TSUD) diagram. Liew et 
al. (2014a) used a similar methodology to propose a new methodology for the grassroots design of heat and 
utility exchanger networks in the TSHI context. Chew et al. (2015) improved the TSHI methodology to consider 
the pressure drop in the pipelines of the utility system due to the process plant locations (horizontal utility 
transfer) and the plant equipment layout design (vertical utility transfer). Bütün et al. (2019) incorporated the 
factors relating to the plant location in the MILP mathematical model, such as distribution heat loss, above 
ground and underground heat loss, the pump works, and piping cost.  
The conventional TSHI methodology could not directly target the energy requirement based on the distribution 
of the utility to various processes across the Total Site boundary. This research proposes a new Pinch-based 
cascade analysis, namely Spatial Utility Problem Table Algorithm (SUPTA), for representing the steady-state 
utility flow in the utility headers. The SUPTA target the energy requirement for each type of utilities individually. 
The cascade analysis is done for distributing the utility from the utility plant (hot oil heaters, boilers, cooling 
towers and chillers) to the farthest located process plant. The methodology considers for the reverse flow 
transfer that happens through rerouting of utility pipelines that is required to satisfy the utility requirement 
located at upstream process. The methodology also considers the possibility to let-down or heat transfer from 
higher to lower temperature utilities. The reverse flow transfer and let-down possibility allow the engineers to 
consider practical limitation at the site. The maximal use of reverse flow transfer and let-down options are 
returning the targeting result to be the same as the conventional TSHI targeting results. This methodology 
could be used for simultaneous targeting and design of site utility distribution system, which could be used to 
consider heat loss and pressure drop on utility headers. In addition, this methodology could directly guide the 
design of the utility network based on TSHI.  

2. Methodology1 
2.1 STEP 1: Data Collection 

The data collection for hot and cold streams information for all the processes within the TSHI boundary, with 
supply temperature, target temperature, heat duty and heat capacity flowrate. The common utility system 
information (temperature) is required to be collected. The locations of the processes must be collected, in 
which the existing utility pipeline design should be known if available.  

2.2 STEP 2: Multiple Utility Problem Table Algorithm (MU-PTA) for each Site/ Process 

The MU-PTA is done in this step to target the utility requirement in a specific process, with maximal energy 
recovery potential assumed (Liew et al., 2018). Therefore, this step assumed that maximal energy recovery is 
achieved within the individual process before considering energy recovery through the utility system in TSHI.  

2.3 STEP 3: Plant Location or Utility Distribution Sequence Identification 

The plant location sequence is identified for a new project. The distance between the process and utility plants 
needs to be known for the design of the utility distribution network. The designer should design a utility 
distribution network for the next step, assuming the utility supply to each plant should be directly from the main 
utility header. The sequence of utility transfer from utility plants should be identified for the existing pipeline. 

2.4 STEP 4: Spatial Utility Problem Table Algorithm (SUPTA) for each Utility Header 

The development of SUPTA is required for each utility header, as shown in Tables 1 and 2, following the 
following steps:  
i. Arrange the process plants from nearest to farthest from the utility plant (Column 1). Record the utility 

requirement as the heat source (positive value - Column 2) or the heat sink (negative value - Column 3). 
Record the energy obtained from let-down from higher temperature utility (Column 4). Calculate Net heat 
requirement (Colum 5) by summing the heat source, heat sink and supply from a let-down station. 

ii. Construct the initial and final cascades (𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖) using Eq. (1) in Column 6 and 7. The initial cascade 
initiates from 0, while the final cascade starts from the absolute value of the most negative value in the 
initial cascade. The Pinch (𝑖𝑖𝑝𝑝𝑖𝑖𝑝𝑝𝑝𝑝ℎ) is located when 0 duty is found in the final cascade  

𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖 = 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖−1 + 𝑁𝑁𝑁𝑁𝑁𝑁𝑖𝑖 (1) 

644



T
a

b
le

 1
: 

S
p
a

ti
a
l 
U

til
ity

 P
ro

b
le

m
 T

a
b

le
 A

lg
o

ri
th

m
(S

U
P

T
A

)
fo

r 
H

o
t 

O
il 

h
e

a
d
e

r
(S

ce
n

a
ri
o

 (
a

))

1
2

3
4

5
6

7
8

9
1

0
1

1
P

la
n

t 
H

e
a

t 
S

o
u

rc
e
  

H
e

a
t 

S
in

k 
L

e
t-

d
o

w
n

a
  

N
e

t 
H

e
a

t 
R

e
q

u
ir

e
m

e
n
t 

(
) 

In
it
ia

l 
H

e
a
t 

C
a

s
ca

d
e
 

(
) 

F
in

a
l H

e
a

t 
C

a
s
ca

d
e
 

(
) 

B
a

la
n
c
e

d
 

C
a

s
ca

d
e
 

(
) 

U
ti
lit

y 
D

e
m

a
n

d
 

(
) 

R
e

v
e

rs
e

 
fl
o

w
 

tr
a

n
s
fe

rb
 

F
in

a
l U

ti
lit

y
 

D
e

m
a

n
d
 

B
o

ile
r

 
 

0
1

,3
9

5
.8

0
A

 
-1

,3
9

5
.8

 
 

-1
,3

9
5

.8
 

-1
3

9
5

.8
 

0
.0

 (
P
in
c
h
)  

0
.0

 (
P
in
c
h
)  

1
,3

9
5

.8
 

-1
,3

9
5

.8
 

 0
 

B
 

1
2

,7
1
8

.5
 

 
 

1
2

,7
1
8

.5
 

1
1

,3
2
2

.7
 

1
2

,7
1
8

.5
 

-8
,8

7
1
.5

 
-3

8
4

7
.0

 
1

,3
9

5
.8

 
-2

,4
5

1
.3

 
C

 
 

 
 

0
 

1
1

,3
2
2

.7
 

1
2

,7
1
8

.5
 

-8
,8

7
1
.5

 
 0

 
  

  
D

0
1

1
,3

2
2

.7
1

2
,7

1
8

.5
-8

,8
7

1
.5

0
E

-7
,9

9
8

.6
-7

,9
9

8
.6

3
,3

2
4

.1
4

,7
1

9
.9

-8
7

2
.9

0
F

0
3

,3
2

4
.1

4
,7

1
9

.9
-8

7
2

.9
0

G
 

 
 

 
0

 
3

,3
2

4
.1

 
4

,7
1

9
.9

 
-8

7
2

.9
 

 0
 

  
  

H
 

 
 

 
0

 
3

,3
2

4
.1

 
4

,7
1

9
.9

 
-8

7
2

.9
 

 0
 

  
  

I
-8

7
2

.9
-8

7
2

.9
2

,4
5

1
.3

3
,8

4
7

.0
0

.0
0

0
J

0
2

,4
5

1
.3

3
,8

4
7

.0
0

.0
0

0
a
re

c
e
iv

e
d

fr
o
m

 h
ig

h
e

r 
te

m
p

e
ra

tu
re

 h
e
a

d
e

r;
b
s
p

e
c
ia

l 
p

ip
in

g
 f

o
r 

re
ve

rs
e
 d

ir
e
ct

io
n

 f
lo

w
a

n
d
 c

ro
s
s
 P

in
c
h

 t
ra

n
sf

e
r,

 g
iv

e
r 

(p
o
si

tiv
e

va
lu

e
)

a
n

d
 r

e
c
e

iv
e

r 
(n

e
g
a

tiv
e

va
lu

e
)

T
a

b
le

 2
: 

S
p
a

ti
a
l 
U

til
ity

 P
ro

b
le

m
 T

a
b

le
 A

lg
o

ri
th

m
 (

S
U

P
T

A
) 

fo
r 

H
o

t 
O

il
h
e

a
d
e

r
(S

ce
n

a
ri
o

 (
b

))

P
la

n
t

H
e

a
t 

S
o

u
rc

e
 

H
e

a
t 

S
in

k
L

e
t-

d
o

w
n

 
N

e
t 

H
e

a
t 

R
e

q
u

ir
e
m

e
n
t

(
)

In
it
ia

l 
H

e
a
t 

C
a

s
ca

d
e

(
)

F
in

a
l H

e
a

t 
C

a
s
ca

d
e

(
)

B
a

la
n
c
e

d
 

C
a

s
ca

d
e

(
)

U
ti
lit

y 
D

e
m

a
n

d
(

)

R
e

v
e

rs
e

 f
lo

w
 

tr
a

n
s
fe

r
F

in
a

l U
ti
lit

y
 

D
e

m
a

n
d

U
ti
lit

y
0

7
,9

9
8

.6
0

E
-7

,9
9

8
.6

-7
,9

9
8

.6
-7

,9
9

8
.6

0
(P

in
c
h
)

0
(P

in
c
h
)

7
,9

9
8

.6
-7

,9
9

8
.6

0
D

0
-7

,9
9

8
.6

0
0

0
C

0
-7

,9
9

8
.6

0
0

0
B

1
,2

7
1
8

.5
1

2
,7

1
8

.5
1

4
,7

1
9

.9
1

2
,7

1
8

.5
-1

,3
9

5
.8

-1
1

,3
2
2

.7
8
,8

7
1

.5
-2

,4
5

1
.3

A
-1

,3
9

5
.8

-1
,3

9
5

.8
3

,3
2

4
.1

1
1

,3
2
2

.7
0

0
U

ti
lit

y
0

8
7

2
.9

0
F

0
0

8
7

2
.9

0
0

G
0

0
8

7
2

.9
0

0
H

0
0

8
7

2
.9

0
0

I
-8

7
2

.9
-8

7
2

.9
-8

7
2

.9
0
(P

in
c
h
)

0
(P

in
c
h
)

8
7

2
.9

-8
7

2
.9

0
J

0
-8

7
2

.9
0

0
0

645



iii. Construct the balanced cascades (𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖) using Eq. (2) in Column 8, in which two similar equations 
are used for the above and below Pinch regions. For the above Pinch region, 𝑈𝑈𝑈𝑈𝑖𝑖𝑈𝑈𝑖𝑖𝑈𝑈𝑈𝑈𝑖𝑖 (Column 9) is added 
when there is a negative value in the 𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖 to make it zero. For the below Pinch region, negative 
𝑈𝑈𝑈𝑈𝑖𝑖𝑈𝑈𝑖𝑖𝑈𝑈𝑈𝑈𝑖𝑖 is added when there is a positive value in the 𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖 to make it zero. 

𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖 = �
𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖−1 + 𝑁𝑁𝑁𝑁𝑁𝑁𝑖𝑖 + 𝑈𝑈𝑈𝑈𝑖𝑖𝑈𝑈𝑖𝑖𝑈𝑈𝑈𝑈𝑖𝑖                            𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑖𝑖 = 0 𝑓𝑓𝑓𝑓𝑓𝑓 𝑖𝑖 ≤ 𝑖𝑖𝑝𝑝𝑖𝑖𝑝𝑝𝑝𝑝ℎ
𝐵𝐵𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖+1 + 𝑁𝑁𝑁𝑁𝑁𝑁𝑖𝑖+1 + 𝑈𝑈𝑈𝑈𝑖𝑖𝑈𝑈𝑖𝑖𝑈𝑈𝑈𝑈𝑖𝑖+1                      𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 max 𝑖𝑖 𝑓𝑓𝑓𝑓𝑓𝑓 𝑖𝑖 ≥ 𝑖𝑖𝑝𝑝𝑖𝑖𝑝𝑝𝑝𝑝ℎ  

 (2) 

iv. The utility demand could be reallocated by reverse flow transfer, which refers to rerouting the utility for 
transferring the utility in a reverse direction. This allows the steam generated from the later process in the 
header to be supplied to the earlier one. Record the transfer in Column 10 with a negative value for the 
supplying process and a positive value for the receiving process. 

v. Calculate the final net utility demand in Column 11 by summing Columns 9 and 10. The positive values in 
this column represent demand from the boiler system, while the negative values indicate excess energy. 
The excess energy could be transferred to a lower temperature header through a let-down station.  

3. Case Study 
The methodology is demonstrated by an illustrative case study developed based on a petrochemical industry, 
with the modified stream and utility information in Tarighaleslami et al. (2017). There are ten processes in the 
case study, and five types of steam utilities serve it. The location or sequence of the plants is hypothetically 
assumed, as shown in Figure 1, with two situations, which are (a) utility plant at the end of the utility header 
and (b) utility plant located at the middle of the utility header. In both scenarios, the distance between the 
process plants and utility plants is assumed at 1 km away. 

  
 Scenario (a) Scenario (b) 

Figure 1: Examples of Utility distribution network, Scenario (a) utility plant at the end of the utility header and 
Scenario (b) utility plant located at the middle of the utility header 

The heat sink and heat source for each process in this case study is done based on STEP 2 and summarised 
in Table 3, which is found using the MU-PTA methodology (Liew et al., 2018). In addition, the total heat source 
and sink available in the Total Site system are determined as mentioned in STEP 3, which the TSHI utility 
requirement targeting result is also summarised in Table 3.  

Table 3: Summary of heat sinks and heat sources for each process 

Process 
Hot oil - HOL  
(kW) 

Very High-
Pressure Steam - 
VHPS (kW) 

High-Pressure 
Steam - HPS 
(kW) 

Medium-Pressure 
Steam - MPS  
(kW) 

Low Pressure  
Steam - LPS  
(kW) 

A 1,395.78 2,439.12 3,532.32 2,466.66 0 
B -12,718.51 -3,987.14 -117.99 -1,603.26 -1,693.5 
C 0 0 3,072.8 248.4 0 
D 0 2,088.9 0 0 296.96 
E 7,998.63 6,848.12 2,532.8 1,606.16 885.15 
F 0 0 0 -464.76 -1,454.52 
G 0 4,109.5 258.18 0 0 
H 0 2,060.054 -132.549 -1,001.729 -585.216 
I 872.85 868.45 -301.3 -1,043.33 -1,818.34 
J 0 0 89.28 3 141.47 
Heat Source 12,719  3,987  552  4,113  5,552  
Heat Sink 10,267  18,414  9,485  4,324  1,324  
TSHI Target 
Requirement  

0 11,976  8,934  211  -4,228  

646



Table 1 shows the SUPTA (as mentioned in STEP 3) for the Hot Oil header under Scenario (a), in which the 
utility plant is located at the end of the header, which 1,395.8 kW of load on the Hot Oil heater, 3,847.0 kW of 
Hot Oil would require to be cool down. The targeted heater load and excess are further reduced to 2,451.3 kW 
of net energy excess by rerouting the piping from plant A to B to recover 1,395.8 kW of energy at the Hot Oil 
level. Meanwhile, Table 2 shows the SUPTA for the Hot Oil header under Scenario (b), in which the utility 
plant is located in between Plant E and F. The targeted Hot Oil heater load is 8,871.5 kW (7,998.6 kW for 
plant E and 872.9 kW for Plant I), while there is an excess of 11,322.7 kW at Plant B. The targeted heater load 
could be reduced by rerouting the Hot Oil from Plant B to Plant E and I, yielding an overall 2,451.3kW of net 
energy excess. It can be easily noticed that the final net energy excess is the same for both scenarios. Still, 
there is an additional piping cost and higher potential energy loss in Scenario 2.    
The targeting result of Scenarios (a) and (b) (shown in Table 4) is the same as the conventional TSHI 
targeting results (Table 3). The let-down and reverse flow arrangements are summarised in Table 4. The 
amount of let-down is the same for Scenarios 1 and 2, also shown in the balanced cascade of the TS-PTA 
methodology. However, the reverse flow configuration differs from Scenarios 1 and 2 because the plant's 
location is the determining factor. In this case study, the amount of utility that needs reverse flow in Scenario 2 
(16,905 kW) is threefold higher than in Scenario 1 (4,248 kW). The high amount of reverse flow indicates more 
capital cost is needed for the utility piping and insulation capital cost.  

Table 4: Result summary for Scenario (a) and (b) 

 Scenario (a) Scenario (b)  
HOL 
(kW) 

VHPS 
(kW) 

HPS 
(kW) 

MPS 
(kW) 

LPS 
(kW) 

HOL 
(kW) 

VHPS 
(kW) 

HPS 
(kW) 

MPS 
(kW) 

LPS 
(kW) 

Final Target 
Net load 0 11,976  8,934  211  0 0 11,976 8,934 211 0 
Net excess 0 0 0 0 4,228  0 0 0 0 4,228 

Let-down -2,451 2,451  0 0 0 -2,451 2,451 0 0 0 
Reverse Flow  1,396 0 345  2,507  0 8,872 3,999 345 2,507 1,182 

Reverse 
flow (kw) 
[Distance 
(km)] 

1,396 
[1] 

- 212[2] 
46[1] 
86[3] 

261[1] 
214[5] 
1,002[7] 
1,040[8] 

- 7,999[3] 
873[8] 

1,910[3] 
2,089[2] 

212[2] 
46[1] 
88[8] 

465[6] 
399[8] 
248[6] 
355[4] 
1,040[5] 

297[2] 
885[3] 

 

MPS Boiler/
Let-down station

(b)

A
(-2,467 kW)

C
(-248 kW)

B
(1,603 kW)

D
(0 kW)

E
(-1,606 kW)

F
(465 kW)

G
(0 kW)

H
(1,002 kW)

J
(-3 kW)

I
(1,043 kW)

1,603 kW 211 kW

211 kW

399 kW864 kW 248 kW

355 kW

3 kW

1,040 kW

Hot Oil Heater

(a)

A
(-1,396 kW)

C
(0 kW)

B
(12,719 kW)

D
(0 kW)

E
(-7,999 kW)

F
(0 kW)

G
(0 kW)

H
(0 kW)

J
(0 kW)

I
(-873 kW)

1,395 kW

7,999 kW 873 kW

Heat transfer station 
to steam system

2,451 kW

 

Figure 2: Design of distribution network in Scenario 2 for (a) Hot Oil and (b) MPS 

For example, the Hot Oil and MPS distribution network through the utility headers in Scenario (b) for the Case 
Study is illustrated in Figure 2. The primary network (solid lines in Figure 2) cannot play a significant function 

647



as the primary energy sources come from the waste heat from other processes at the downstream in the 
system. The extra reverse flow piping system (dotted lines in Figure 2) increases the company's capital cost. 
In addition, it might represent a higher heat loss and pressure drop in the utility pipelines, which are subject to 
be optimised based on the situation. This result also indicates overall header flow direction could be reversed 
to minimise the reverse flow pipelines. 

4. Conclusion 
The flow direction of the utility headers is ignored in the Pinch-based TSHI methodology for targeting the 
energy requirement for energy recovery across multiple processes or plants. The Spatial Utility Problem Table 
Algorithm (SUPTA) is a Pinch-based Cascade Analysis proposed in this work for simultaneous targeting and 
designing the utility distribution system. The energy cascade in SUPTA is done according to the industrial 
process location. The exact location for the let-down station and reverse flow pipelines could be easily 
identified using SUPTA. The methodology could be extended for future research to incorporate the energy 
loss and pressure drops in the targeting results. 

Acknowledgements 

The authors would like to thank you for the financial support from Universiti Teknologi Malaysia through the 
UTM Encouragement Research Grant (Q.K130000.3843.31J02). The research has also been supported by 
the Sustainable Process Integration Laboratory SPIL project, funded as project No. 
CZ.02.1.01/0.0/0.0/15_003/0000456, the Operational Programme Research, Development and Education of 
the Czech Ministry of Education, Youth and Sports by EU European Structural and Investment Funds, 
Operational Programme Research, Development and Education under a collaboration agreement with UTM, 
Malaysia. 

References 

Boldyryev S., Shamraev A.A., Shamraeva E.O., 2021, The design of the total site exchanger network with 
intermediate heat carriers: Theoretical insights and practical application, Energy, 223, 120023. 

Butturi M.A., Lolli F., Sellitto M.A., Balugani E., Gamberini R., Rimini B., 2019, Renewable energy in eco-
industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis, Applied 
Energy, 255, 113825. 

Bütün H., Kantor I., Maréchal F., 2019, Incorporating Location Aspects in Process Integration Methodology, 
Energies, 12(17), 3338. 

Chew K.H., Klemeš J.J., Alwi S.R.W., Manan Z.A., Reverberi A.P., 2015, Total Site Heat Integration 
Considering Pressure Drops, Energies, 8(2), 1114-1137. 

Chew K.H., Klemeš J.J., Wan Alwi S.R., Abdul Manan Z., 2013, Industrial implementation issues of Total Site 
Heat Integration, Applied Thermal Engineering, 61(1), 17-25. 

Klemeš J.J., Varbanov P.S., Walmsley T.G., Jia X., 2018, New directions in the implementation of Pinch 
Methodology (PM), Renewable and Sustainable Energy Reviews, 98, 439-468. 

Kröhling D.E., Mione F., Hernández F., Martínez E.C., 2022, A peer-to-peer market for utility exchanges in 
Eco-Industrial Parks using automated negotiations, Expert Systems with Applications, 191, 116211. 

Liew P.Y., Alwi S.R.W., Klemeš J.J., Varbanov P.S., Manan Z.A., 2014a, Utility-Heat Exchanger Grid 
Diagram: A tool for designing the total site heat exchanger network, Chemical Engineering Transactions, 
39. 

Liew P.Y., Theo W.L., Wan Alwi S.R., Lim J.S., Abdul Manan Z., Klemeš J.J., Varbanov P.S., 2017, Total Site 
Heat Integration planning and design for industrial, urban and renewable systems, Renewable and 
Sustainable Energy Reviews, 68, 964-985. 

Liew P.Y., Wan Alwi S.R., Ho W.S., Abdul Manan Z., Varbanov P.S., Klemeš J.J., 2018, Multi-period energy 
targeting for Total Site and Locally Integrated Energy Sectors with cascade Pinch Analysis, Energy, 155, 
370-380. 

Liew P.Y., Wan Alwi S.R., Klemeš J.J., 2014b, Total Site Heat Integration Targeting Algorithm Incorporating 
Plant Layout Issues, Computer Aided Chemical Engineering, 33, 1801-1806. 

Tarighaleslami A.H., Walmsley T.G., Atkins M.J., Walmsley M.R.W., Liew P.Y., Neale J.R., 2017, A Unified 
Total Site Heat Integration targeting method for isothermal and non-isothermal utilities, Energy, 119, 10-
25. 

 

648


	PRES22_0217.pdf
	Spatial Total Site Heat Integration Targeting using Cascade Pinch Analysis