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Centralised utility system planning for a Total Site Heat Integration network
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Centralised utility system planning for a Total Site Heat Integration network Peng Yen Liew a , Sharifah Rafidah Wan Alwi a,∗ , Petar Sabev Varbanov b , Zainuddin Abdul Manan a , Jiˇrí Jaromír Klemeˇs b a
Process Systems Engineering Centre (PROSPECT), Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia ˝ Centre for Process Integration and Intensification – CPI2 , Research Institute of Chemical and Process Engineering – MUKKI, Faculty of IT, University of Pannonia, Egyetemu. 10, H-8200 Veszprém, Hungary b
a r t i c l e
i n f o
Article history: Received 22 September 2012 Received in revised form 6 February 2013 Accepted 13 February 2013 Available online xxx Keywords: Total Site Heat Integration Pinch Analysis Total Site Sensitivity Table Sensitivity analysis Utility production planning
a b s t r a c t Total Site Heat Integration (TSHI) is a technique of exchanging heat among multiple processes via a centralised utility system. An analysis of the integrated multiple processes, also known as the Total Site (TS) system sensitivity, is needed to characterise the effects of a plant maintenance shutdown, to determine the operational changes needed for the utility production and to plan mitigation actions. This paper presents an improved Total Site Sensitivity Table (TSST) to be used as a systematic tool for this purpose. The TSST can be used to consider various ‘what if’ scenarios. This tool can be used to determine the optimum size of a utility generation system, to design the backup generators and piping needed in the system and to assess the external utilities that might need to be bought and stored. The methodology is demonstrated by using an Illustrated Case Study consisting of three processes. During the TS normal operation, the Total Site Problem Table Algorithm (TS-PTA) shows that the system requires 1065 kW of High Pressure Steam and 645.5 kW of Medium Pressure Steam as the heating utility, while for the cooling utility, 553.5 kW of Low Pressure Steam and 3085 kW of cooling water are required. The results of the modified TSST proposed that a boiler and a cooling tower with the system design requiring a maximum capacity of 2.172 MW of steam and 4.1865 MW of cooling water are needed to ensure an operational flexibility between the three integrated processes. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Beginning in the 1970s, research on maximising heat recovery using the Pinch Analysis technique has grown rapidly. Building upon the analysis designed for a single plant heat recovery system, previous works have also explored the potential of integrating the heat requirements for multiple plants via a centralised utility system, further reducing the utility requirements in industry and producing integrated community systems. This analysis is known as the Total Site Heat Integration (TSHI). The TSHI concept was first introduced by Dhole and Linnhoff (1993). This integration method offers a greater energy savings opportunity compared with the focus on the single processes. The Site Sink-Source Profiles (SSSP) are composite profiles derived from the combined Grand Composite Curves (GCCs) of the individual processes. SSSP could be divided into site source and sink profile. The site source profile is the total energy available in all processes, while the site sink profile shows
∗ Corresponding author. Tel.: +60 07 5535533; fax: +60 07 5581463. E-mail addresses: [email protected], sr [email protected] (S.R. Wan Alwi).
the total energy requirement in the processes. These profiles were introduced by Dhole and Linnhoff (1993) and Raissi (1994) to target the overall energy requirements for the Total Site system. Klemeˇs, Dhole, Raissi, Perry, and Puigjaner (1997) extended the targeting method to include the Total Site Profile (TSP), the Site Composite Curves (SCC) and the Site Utility Grand Composite Curve (SUGCC). For the same concept, the TSP is synonymous with a SSSP, while the SCC are constructed by performing Multiple Utility (MU) targets on the TSP. The SUGCC is a form of the site composite, providing valuable insights on the cogeneration potential for the Total Site (TS). These tools have significantly impacted the development of the TSHI technique. To reduce the carbon footprint, Perry, Klemeˇs, and Bulatov (2008) have conceptually extended the TSHI by integrating large community servicing with corporate buildings as additional heat sinks and renewable energy as heat sources. The inherent variability in the heat supply and demand increased the difficulty in both handling and controlling the system. Varbanov and Klemeˇs (2011) later introduced into the Total Site description the Time Slices with a heat storage system for handling the variable supply and demand in the TSHI using the heat integration of the individual batch processes. In the same paper, the Total Site Heat
0098-1354/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.compchemeng.2013.02.007
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Nomenclature TS TT T T CHP CW GCC HPS LIES LPS mCp MU MU-PTA PTA Qcmin Qhmin SCC SDN SUGCC SSSP TS TSP TSHI TSST TSUD TS-HSC TS-PTA DH Tmin,pp Tmin,up
initial supply temperature (◦ C) final target temperature (◦ C) shifted temperature (◦ C) double-shifted temperature (◦ C) Combined Heat and Power cooling water Grand Composite Curve high-pressure steam Locally Integrated Energy Sector low-pressure steam heat capacity flowrate (kW/◦ C) multiple utility Multiple Utility Problem Table Algorithm Problem Table Algorithm minimum cooling requirement (kW) minimum heating requirement (kW) Site Composite Curve Steam Distribution Network Site Utility Grand Composite Curve Site Sink-Source Profile Total Site Total Site Profile Total Site Heat Integration Total Site Sensitivity Table Total Site Utility Distribution Total Site Heat Storage Cascade Total Site Problem Table Algorithm Stream Heat Load (kW) minimum temperature difference between process stream (◦ C) minimum temperature difference between utility and process streams (◦ C)
Cascade was introduced for visualising the heat flows across processes, the steam system and the heat storage system. Wan Alwi, Liew, Varbanov, Manan, and Klemeˇs (2012) introduced a numerical solution for the TSHI system to address the variable availability. This work presented a Total Site Heat Storage Cascade (TS-HSC) to address the heat storage facilities required by the TS system. Nemet, Klemeˇs, Varbanov, and Kravanja (2012) discussed the approaches needed to maximise the use of the renewable energy sources with a fluctuating supply. They introduced a framework for the integration of the chemical processes with solar energy, allowing a user to determine the amount of potential solar thermal energy that could be used within a process. Varbanov, Fodor, and Klemeˇs (2012) revisited the global minimum temperature difference (Tmin ) used in the previous method. This work suggested that the values for Tmin should be specified for each process on the site individually. They demonstrated that the assumption of a global Tmin for the entire Total Site may have been oversimplified, leading to inadequate results with the imprecise estimation of the overall Total Site heat recovery targets. The modified Total Site targeting procedure proposed in the paper allowed for more realistic heat recovery targets for the Total Sites to be targeted. A graphical approach was used in the early stages of the TS targeting, including the TSP, the SCC, the SUGCC construction (Klemeˇs et al., 1997), the TS targeting methodology for both industrial processes and renewable energy sources (Perry et al., 2008) and the TS targeting methodology with both process and utility specific Tmin (Varbanov et al., 2012). Liew, Wan Alwi, Varbanov, Manan, and Klemeˇs (2012) recently introduced an alternative approach
based on a numerical method known as the Total Site Problem Table Algorithm (TS-PTA) to target the Total Site utility requirement. This method is easier to construct, giving faster and more accurate results compared to the graphical approach, which has a tendency to include a graphical error with the curve shifting. The Total Site Utility Distribution (TSUD) Table was also introduced to visualise the heat flows between the processes and the utility system. A numerical tool, the Total Site Sensitivity Table (TSST), to explore the site sensitivity was also proposed in the same paper. There are several mathematical models for the plant utility system planning process that incorporate the TSHI theory. Mavromatis and Kokossis (1998) introduced models for a steam system in the TSHI with two main objectives, the selection of the pressure steam levels and the determination of the operating unit configuration for the steam levels. A new methodology was developed by Halasz, Nagy, Ivicz, Friedler, and Fan (2002) for the optimal retrofit synthesis and operation of the steam-supply system of a chemical complex with production capacities for a multitude of products that vary temporarily. Marechal and Kalitventzeff (2003) proposed optimisation models for solving a multi-period problem that incorporated the selection and target for the optimum operational strategy for a utility system. A top-level analysis (Varbanov, Perry, Makwana, Zhu, & Smith, 2004) is another mathematical modelling methodology that can be used for these concepts. This method allows for “scoping”, i.e., selecting the site processes to target for the heat integration improvements. The current steam and power demands can be optimised and the potential benefit of reducing the steam demand can be assessed. A set of curves for the steam marginal prices can be produced for the system under consideration via a top-level analysis. Chen and Lin (2011) proposed a systematic optimisation approach to design a Steam Distribution Network (SDN) of the steam systems to obtain an improved energy utilisation in the network. In this model, the operating conditions of the SDN were treated as design variables to be optimised. In another development on the TSHI, Bandyopadhyay, Varghese, and Bansal (2010) proposed a simplified methodology to target the cogeneration potential based on the Salisbury (1942) approximation. This method is simple and linear, using the rigorous energy balance at the steam header. Kapil, Bulatov, Smith, and Kim (2012)introduced a new model based on an isentropic expansion. These model results were favourable compared with the results from the detailed isentropic design methods. This method also included an optimisation study, which systematically determined the levels of the steam mains, subjected to economic parameters and constraints. The TSST was first proposed by Liew et al. (2012). The tool could be used to systematically determine the minimum and maximum boiler and cooling utility capacities at different operating conditions. However, the tool has a major assumption, which treated the hot utility and the cold utility as the same type of utility. For example, the “Difference from normal operation” should not be calculated for the scenario when the Low Pressure Steam (LPS) consumption for the base case are located at different Pinch regions. This is because the steam generated cannot be used to satisfy the cooling requirement at the same steam level. Furthermore, the tool can be further developed to explore the potential of cascading the excess energy at high temperature to satisfy the LPS requirement during the process operational change scenario. In the method proposed previously, the maximum and minimum boiler capacities are also not determined in a systematic way via the TSST. The potential worst case scenario was also not identified as there was no specific ways to determine the numbers of “what if” scenarios. In this paper, the limitations faced by the TSST methodology introduced by Liew et al. (2012) is addressed and the tool is improved to include the insights and guidelines generated from the
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TSHI utility production system planning process. This tool is able to determine the worst case scenario, the maximum capacity and the turn-down ratio for each type of utility supply for multiple scenarios. This approach also allows for a more flexible plant operation with a low Total Site sensitivity towards operational disturbances. The effects of a process disruption within a Total Site can be analysed with this tool to allow contingency plans and actions to be taken to avoid disruptions in the other processes that are integrated in the system. The process disruptions may include shutdowns of one or more plants, a scheduled maintenance, production changes or emergency cases. 2. Methodology The proposed methodology for the improved Total Site Sensitivity Table (TSST) is defined in the following steps. 2.1. Step 1: stream data determination The hot and cold stream data for the individual plants that would be integrated in the Total Site system are determined. This process includes the supply and target temperature data, the fluid flow rate and the heat capacity data, information that is essential for a Pinch Analysis study. The existing utility temperature levels from the centralised utility system are also determined. 2.2. Step 2: TS utility requirement determination Once the data are determined, the Total Site Heat Integration analysis can be performed by using either the established graphical or the numerical approach. The TSHI analysis involves the targeting of the individual plant heat recovery potential and the determination of the loads and levels of utilities that can be generated below the Pinch region (as TS heat sources) and used to satisfy the heat requirements (TS sinks) above the Pinch region. The determination of the steam requirements for these multiple utility levels can be obtained by using either the Grand Composite Curves (GCC) with the Total Site Profile (TSP) introduced by Klemeˇs et al. (1997) or the Multiple Utilities Problem Table Algorithm (MU-PTA) by Liew et al. (2012). The optimum utility levels are determined by varying the steam saturation temperature or pressure on the established tools. These TS sources and sinks streams are then composited and the TS minimum multiple utility target after the TS heat recovery can be determined using either the Site Composite Curve (SCC) with the Site Utility Grand Composite Curve (SUGCC) (Klemeˇs et al., 1997) or by a numerical approach through the Total Site Problem Table Algorithm (TS-PTA) (Liew et al., 2012). 2.3. Step 3: Total Site Sensitivity Table (TSST) construction The TSST is a useful tool, demonstrating the effect of plant shutdowns or operability on the TS utility generation and requirements. The following methodology components can be used to construct the improved sensitivity analysis tool. 2.3.1. Determining the numbers of possible scenarios The possible scenarios for a shutdown for either a single plant or multiple plants can be estimated using Eq. (1). This equation can accurately determine the number of scenarios (Sn ) needed to be examined in the TSST as a function of the number of plants (n) integrated in the TS. In this equation, the effect of a total plant shutdown is assumed to be the consequences derived from the worst case scenario. As an example, for three integrated plants, Plants A, B and C, the seven potential scenarios in the TS analysis would be:
3
Scenario 1: All plants in full operation (base case) Scenario 2: Plant A shutdown, Plants B and C in operation Scenario 3: Plant B shutdown, Plants A and C in operation Scenario 4: Plant C shutdown, Plants A and B in operation Scenario 5: Plants A and B shutdown, Plant C in operation Scenario 6: Plants A and C shutdown, Plant B in operation Scenario 7: Plants B and C shutdown, Plant A in operation Sn =
1 3 5 n + n n = 2, 3, 4, 5 . . . 6 6
(1)
where S, number of scenarios; n, number of plants/processes. 2.3.2. Obtaining the TS targets for all possible scenarios Step 2 is repeated to obtain the utility requirement for the Total Site system for the possible scenarios. To do this, the source and the demand data of the plant being shut down are omitted in the construction of the TSP or the TS-PTA. 2.3.3. Recording the TS target at utility levels with storage facilities The requirements for the different types of utilities during the different scenarios are recorded in the TSST. The value for the hot utility (MU above the TS Pinch point) is recorded without bracket, while the value for the cold utility (MU below the TS Pinch Point) is recorded in a square bracket to emphasise the differences. The location of the TS Pinch Point is also noted. 2.3.4. Determining the requirement difference of base case and each scenario Next, the effect of the variations between the base case with all plants operating normally and the various possible scenarios for the TS centralised utility system needs to be analysed. For the cases in which the multiple utility for the base case and the Scenario i is located in the same Pinch region (either both above the Pinch or both below the Pinch), the difference between the Scenario i and the base case utility can be calculated using Eq. (2) for each utility type j: MUDifference,j = MUbase−case,j − MUSi,j
(2)
where MUDifference,j , multiple utility variations between the base case and the scenario for the Utility j; MUbase-case,j , multiple utility of the base case for the Utility j; MUSi,j , multiple utility of the Scenario i for the Utility j. A positive difference indicates that there is an excess utility produced by the boiler houses or the chilling units compared with the base case scenario, while a negative difference represents a deficit in the external utility. For scenarios where the MUbase-case,j and the MUSi,j are located at different Pinch regions, the utility was changed from a hot to a cold utility requirement or vice versa. For example, for the MUbase-case,j located above the Pinch, this situation would require a Low Pressure Steam (LPS) as the hot utility. With the MUSi,j located below the Pinch, the situation does not require a LPS, but rather generates a LPS that will require the stream to be cooled down with cooling water. This scenario indicates that the centralised utility system will have an excess LPS from the boiler during Scenario i, generating an LPS from the process without a reduction in the boiler capacity. This situation would result in a double cooling utility needed during Scenario i. A summary of the Scenario analysis is as follows: (i) If the MUbase-case,j is located above the Pinch and the MUSi,j is located below the Pinch, more cold utility will be required. The calculation of the difference is required to determine both the heating and the cooling utility. For the heating utility, MUDifference,j = −MUbase−case,j
(3)
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Table 1 Stream data for Processes A, B and C.
For the cooling utility MUDifference,j = MUSi,j
(4)
(ii) If the MUbase-case,j is located below the Pinch and the MUSi,j is located above the Pinch, the cold utility produced is not needed, but extra steam for heating is required in this scenario. Eq. (4) can be used to determine the difference of the heating utility, while the difference for the cooling utility could be determined by Eq. (3). 2.3.5. Obtaining the difference after cascade The third step in the TSST is to calculate the “difference after cascade”. For the hot utility, the excess is kept at the highest level with the deficit at the lowest level. For the cold utility, the deficit is kept at the lowest temperature with the excess at the original utility level. This value could be determined using the heuristic below:
Stream Process A A1 hot A2 hot A3 cold A4 hot Process B B1 hot B2 hot B3 cold B4 cold Process C C1 hot C2 cold C3 cold C4 cold
TS (◦ C)
TT (◦ C)
H (kW)
mCp (kW/◦ C)
T S (◦ C)
TT (◦ C)
200 150 50 170
100 60 220 150
2000 3600 −2550 1000
20 40 15 50
190 140 60 160
90 50 230 140
200 200 30 130
50 119 200 150
450 1863 −680 −300
3 23 4 15
190 190 40 140
40 109 210 160
240 50 40 109
100 250 190 140
210 −400 −1500 −186
1.5 2 10 6
230 60 50 119
90 260 200 150
3.1. Step 1: steam data extraction • For an excess utility (positive MUDifference,j ) above the TS Pinch location in a scenario, this value is cascaded down to the lower utility level with a heating utility deficit (negative difference) to form the “difference after cascade”. As the higher hot utility levels (e.g., HPS) are typically more expensive than the lower hot utility levels (e.g., MPS), the lower temperature hot utilities are preferred to be cascaded downward to the heating utility deficit, ensuring that the production of the higher temperature utility can be reduced to reduce operating costs. For a heating utility in excess of 200 kW of HPS and 100 kW of MPS, a value of 200 kW for the LPS would be insufficient in this case. The total of 300 kW of the higher utility level could be let down to the LPS level, but with only 100 kW of the MPS and the HPS available to be let down to the LPS level. The net utility excess of 100 kW could remain in the HPS to ensure that this high quality heat could be sold or the heating utility generation can be reduced. • For the scenarios below the TS Pinch region, the deficit of the cooling utility (the negative difference in brackets) for the steam generation can be cascaded downwards to the cooling water level as there is no need to generate steam without a requirement. The generation of the unused steam would only require an additional boiler capacity with the excess heat being removed with cooling water. 2.3.6. Determining the storage capacity required The capacity requirements for the centralised utility system can be summarised using the results from each scenario: • The maximum requirement for each type of utility can be calculated by adding the absolute value of the most negative number in the “difference after cascade” with the utility requirement at normal operating conditions. With no negative values, the maximum utility requirement would be equal to the normal operation utility. • The minimum steam utility requirement for each type of utility can be calculated by deducting the most positive value of the “difference after cascade” from the utility requirement at normal operating conditions. The utility requirement during normal operations would be used for the cases without a positive difference.
3. Case study The construction of the Total Site Sensitivity Table (TSST) is illustrated using a case study.
The Illustrative Case Study consisted of three process units, Processes A, B, and C, as shown in Table 1. The minimum temperature difference between the process streams (Tmin,pp ) and the minimum temperature difference between the process streams and the utility (Tmin,up ) were assumed to be 20 ◦ C and 10 ◦ C, respectively. The existing available on site utilities were High Pressure Steam (HPS) at 270 ◦ C, Medium Pressure Steam (MPS) at 180 ◦ C, Low Pressure Steam (LPS) at 133 ◦ C and cooling water (CW) at 15–20 ◦ C. The simplified utility system configuration is presented in Fig. 1. A natural gas fuelled boiler was used to produce the HPS to satisfy the site steam demand. The reduction of the steam production from the boiler would directly contribute to the carbon emission reduction of the site. Steam can also be produced from the removal of heat from the high temperature process stream. For example, the oil and gas processing industries typically employ very high temperature processes, generating both HPS and MPS at the processing site. The HPS produced from the boiler house or the processes could be stepped down to a lower energy level through a turndown valve or a steam turbine. Industries with excessive amounts of high temperature heat have frequently used steam turbines in their steam systems to generate electricity. The condensate from the used steam can be sent back to a de-aeration tank to eliminate dissolved oxygen to prevent corrosion. 3.2. Step 2: TS utility requirement determination In the next step, the Multiple Utility Problem Table Algorithm (MU-PTA) by Liew et al. (2012) was used to target the external multiple utility requirements for each individual process. Table 2 shows a sample MU-PTA for Process A. Process A had the potential to generate 50 kW MPS and 1515 kW LPS, requiring 3085 kW of cooling water. This information can be used to contribute to the
Boiler Houses HPS MPS LPS CW
De-aerator
Process A
Process B
Process C
Fig. 1. Total Site with a centralised utility system (after Klemeˇs et al., 2010).
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Table 2 MU-PTA for Process A.
mCp (kW/oC)
T’
T”
ΔT
(oC)
(oC) 270
(oC)
230
230
190 190
190 190 180
160
160
140
140 133
90
90
60
60
50
50
20
20
20
40
15
mCp
50
(kW/oC) (kW)
0
0
0
40
-15
-600
10
5
50
20
5
100
20
55
1100
7
45
315
43
45
1935
30
25
750
10
40
400
30
0
0
Table 3 Summary of multiple utility targets for each process in the Total Site.
Process HPS MPS LPS CW
Below Pinch (heat source) [kW]
Above Pinch (heat sink) [kW]
A
A
B
C
600
180 100
285 595.5 995.5
50 1515 3085
B
C
34
Initial Cascade (kW) 0
ΔH
MU Cascade (kW) 0
600
0
0 0
0 0
50
0
150
0
1250
0
1565
0
3500
0
4250
0
4650
0
4650
0
Utility Requirement (kW) HPS 600
600 PINCH -50 MPS
50
LPS
1515
CW
3085
-100 -1100 -315 -1935 -750 -400 0
The TS-PTA method by Liew et al. (2012) was used to target the Total Site multiple utility. Table 4 shows the TS-PTA for the base case scenario. In order to illustrate the utility consumption and generation, TSP and SCC are plotted based on the TS-PTA (Table 4). Fig. 2 shows the TSP and SCC for the Illustrative Case Study. The TS Pinch point was located between the LPS and the CW. A multiple utility targeting on the TS-PTA demonstrated that the system required 1065 kW of HPS and 645.5 kW of MPS as the heating utility for the entire TS. For the cooling utility, 553.5 kW of LPS and 3085 kW of CW was required. The SDN for the integrated TS system in the Illustrative Case Study is shown in Table 5, the Total Site Utility Distribution (TSUD) Table. These values were recorded in the second column of the TSST as shown in Table 6.
TS heat sources. Process A also required 600 kW of HPS for heating, representing the TS heat sinks. MU-PTA was also performed for Processes B and C. Table 3 summarises the multiple utility targets for each process.
Table 4 Total Site Problem Table Algorithm (TS-PTA) for the Illustrative Case Study on normal operation. 1 Utility
2 Heat source (kW)
HPS MPS
50
3 Heat sink (kW)
4 Heat requirement (kW)
1065
−1065
695.5
5 Initial cascade (kW)
6 Final cascade (kW)
7 MU cascade (kW)
0
1710.5
0
−1065
645.5
0
0
0
−1157
553.5
0
1928
3638.5
0
1065
−645.5 −1710.5
LPS
1549
CW
3085
995.5
8 Utility requirement (kW)
645.5 TS Pinch −553.5
553.5
−3085
3085
Table 5 Total Site Utility Distribution (TSUD) Table for the Illustrative Case Study.
Process A
Heat Source [kW] Process Process B C
HPS MPS
50
LPS
1,515
CW
3,085
Site Utility
Process A
1,065
600
645.5 34
Heat Sink [kW] Process Process B C 180
285
100
595.5 995.5
Site Utility
553.5 3,085
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Scenario 2 (Processes B and C in operation)
Scenario 3 (Processes A and C in operation)
Scenario 4 (Processes A and B in operation)
Utility
Requirement (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
1065
465
600
0
885
180
180
780
285
285
645.5 Pinch
695.5
−50
0
545.5 Pinch
100
100
50 Pinch
595.5
595.5
961.5
−961.5 [553.5]
−411.5 [553.5]
[519.5]
[34]
[34]
[1549]
[−995.5]
[0]
[3085]
[3085]
[3085]
[0]
[0]
[3085]
[0]
[−995.5]
(a) HPS MPS LPS
[553.5] CW
Pinch [0]
[3085]
Scenario 1 (all processes in operation – base case)
Scenario 5 (Process A in operation)
Scenario 6 (Process B in operation)
Scenario 7 (Process C in operation)
Summary
Utility
Requirement
Requirement
Difference
Difference after cascade
Requirement
Difference
Difference after cascade
Requirement
Difference
Difference after cascade
Maximum requirement
Minimum requirement
(b) HPS
1065
600 Pinch
465
99
180
885
885
285
780
0
1065
180
MPS
645.5
645.5 [−50]
645.5 [0]
100
545.5
545.5
595.5
50
0
695.5 [0]
0 [0]
995.5
−995.5 [553.5]
−165.5 [553.5]
411.5 [553.5]
0 [0]
[3085]
[3085]
[4186.5]
[0]
[50] Pinch
Pinch
LPS
CW
[553.5]
[1515]
[−961.5]
[0]
[34]
[519.5]
[519.5]
[3085]
[3085]
[0]
[−1011.5]
[0]
[3085]
[3085]
Pinch [0]
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Scenario 1 (all processes in operation – base case)
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Table 6 Total Site Sensitivity Table (TSST).
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HPS 250
200
MPS
150
Site Source Profile
LPS Site Sink Profile
100
50
CW
0
-6000
-5000
-4000
-3000
-2000
-1000
0
1000
2000
3000
4000
Fig. 2. Total Site Profile (TSP) and Site Composite Curves (SCC) for the Illustrative Case Study.
3.3. Step 3: Total Site Sensitivity Table (TSST) construction For the three processes involved in this Illustrative Case Study, the number of possible scenarios involving process shut downs is equal to seven, as suggested by Eq. (1). The TS-PTAs for each scenario were constructed. The multiple utility targets with the TS Pinch location are listed in Table 6. The differences between the normal operating conditions and the various scenarios of the TS utilities requirement are determined based on above or below TS Pinch location, by using Eqs. (2)–(4) (as explained in Section 2.3). This step is corrected from the difference calculation without considering the location of TS Pinch in the previous published methodology in Liew et al. (2012). For example, the TS Pinch location changed from a point between the MPS and the LPS for the base case to a point between the LPS and the CW for Scenario 2. The difference between the base case and Scenario 2 for the HPS, the MPS and the CW can be calculated directly using Eq. (2), as these values are located in the same Pinch region. These values are given in Column 4, Table 6a. The positive difference indicated that the boiler was producing an excess of 600 kW of the HPS and the cooling tower had an excess of 3850 kW of the CW that was not used during Scenario 2. The negative difference indicated there was a deficit of 50 kW of MPS that was needed to be generated. For the LPS, the utility location changed from below the Pinch (base case) to above the Pinch (Scenario 2). The previous methodology by Liew et al. (2012) is expected to yield 408 kW of extra LPS requirement in Scenario 2. However, the extended TSST in this paper indicates that the system requires an additional boiler to generate the LPS instead. The negative difference indicated a deficit of 961.5 kW in the LPS. The additional CW was added at the CW difference row. The “difference after cascade” was calculated for each of the scenarios. The excess heating utility, which is represented by a positive difference, can be cascaded towards the lower steam utility level characterised by a negative difference for the point above the Pinch region. This type of heat recovery is not included in the previous published TSST (Liew et al., 2012) methodology. In Scenario 2, Process A can be shut down due to a scheduled maintenance. This shutdown would not need the 600 kW HPS generated from the centralised utility system for Process A during the base case, while increased levels of the MPS and the LPS would be needed to satisfy the requirements for Processes B and C. To minimise the changes in the boiler utility generation, the excess unused HPS (indicated by a positive difference) can be cascaded downwards to satisfy the deficits in the MPS and the LPS. This cascade would allow the HPS and the MPS boiler to run as usual, with only an additional
7
411.5 kW LPS needed to be generated. For the points below the Pinch region, there is only one utility type (CW) in excess, indicating that the 3085 kW CW production would need to be shutdown during Scenario 2. After analysing the various ‘what if’ scenarios in the TSST, the TS system in this demonstration case study required a natural gas powered boiler with a maximum capacity of 2172 kW of superheated HPS production. The superheated steam generated with this system could be stepped down to 1065 kW of HPS, 695.5 kW of MPS and 411.5 kW of LPS, compared with the 1710 kW of total steam required during normal operations. A backup boiler may be a good option to cater to these production changes or the steam requirement may also be obtained externally. In the most extreme case, the minimum total steam requirement for the TS system was 180 kW during Scenario 6, as shown in Table 6b. For instance, the boiler in the TS required a turn down ratio of not less than 50%, assuming the lowest capacity of the boiler to be 1086 kW. These conditions would suggest that the remaining 906 kW of steam needed to be cooled down using cooling water or sold to other plants. Another alternative would be to divert the excess steam production for the Combined Heat and Power (CHP) system to generate more power. Another choice could also include dividing the capacity between two boilers, allowing the boiler capacity to be manipulated based on the equipment restrictions. For the cooling water, the maximum capacity required was 5092.5 kW. An additional 4186.5 kW for the maximum capacity and 906 kW of steam generated was required due to the limitations from boiler’s turn down ratio. The minimum capacity for the cooling tower was 0 kW. 4. Conclusion The Total Site Sensitivity Table (TSST) has been extended for planning the TSHI centralised utility system. This approach provides insights on the consequences of a plant shutdown or process upsets on the entire TS system integration and the centralised utility system. By identifying heating or cooling utility requirements during a plant shut down, a suitable size utility system can be planned to ensure a flexible and undisrupted operation for the integrated processes. These decisions must be balanced with the operational challenges as well as the capital and operating costs. The proposed tool is able to determine the optimal design and operation of the centralised utility system by assuming 100% efficiency for the utility system. This is actually not representing the actual situation. For the future work, the effect of load changes on the TS utility system efficiencies can be further investigated. For example, the turbine and boiler efficiencies are affected by their loads (Möller, Genrup, & Assadi, 2007; Zhou, Liu, Li, Pistikopoulos, & Georgiadis, 2013). Hence, the off-design operation may require special considerations during the utility system sizing. Acknowledgements The authors would like to thank the Ministry of Higher Education (MOHE) Malaysia and the UTM in providing the research funding for this project under Vote No. Q.J130000.2544.03H44 and the EC supported project Energy – 2011-8-1 Efficient Energy Integrated Solutions for Manufacturing Industries (EFENIS) – ENER/FP7/296003/EFENIS. References Bandyopadhyay, S., Varghese, J., & Bansal, V. (2010). Targeting for cogeneration potential through total site integration. Applied Thermal Engineering, 30, 6–14. Chen, C., & Lin, C. (2011). A flexible structural and operational design of steam systems. Applied Thermal Engineering, 31, 2084–2093.
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Dhole, V. R., & Linnhoff, B. (1993). Total site targets for fuel, co-generation, emission and cooling. Computers and Chemical Engineering, 17, 101–109. Halasz, L., Nagy, A. B., Ivicz, T., Friedler, F., & Fan, L. T. (2002). Optimal retrofit design and operation of the steam-supply system of a chemical complex. Applied Thermal Engineering, 22, 939–947. Kapil, A., Bulatov, I., Smith, R., & Kim, J. (2012). Site-wide low-grade heat recovery with a new cogeneration targeting method. Chemical Engineering Research and Design, 90(5), 677–689. Klemeˇs, J., Dhole, V. R., Raissi, K., Perry, S. J., & Puigjaner, L. (1997). Targeting and design methodology for reduction of fuel, power and CO2 on total site. Applied Thermal Engineering, 7, 993–1003. Klemeˇs, J., Friedler, F., Bulatov, I., & Varbanov, P. (2010). Sustainability in process industry: Integration and optimization. New York, US: McGraw Hill. Liew, P. Y., Wan Alwi, S. R., Varbanov, P. S., Manan, Z. A., & Klemeˇs, J. J. (2012). A numerical technique for Total Site sensitivity analysis. Applied Thermal Engineering, 40, 397–408. Marechal, F., & Kalitventzeff, B. (2003). Targeting the integration of multi-period utility systems for site scale process integration. Applied Thermal Engineering, 23, 1763–1784. Mavromatis, S. P., & Kokossis, A. C. (1998). Conceptual optimisation of utility networks for operational variations: I. Targets and level optimisation. Chemical Engineering Science, 53(8), 1585–1608. Möller, B. F., Genrup, M., & Assadi, M. (2007). On the off-design of a natural gas-fired combined cycle with CO2 capture. Energy, 32, 353–359.
Nemet, A., Klemeˇs, J. J., Varbanov, P. S., & Kravanja, Z. (2012). Methodology for maximising the use of renewables with variable availability. Energy, 44(1), 29–37. Perry, S., Klemeˇs, J., & Bulatov, I. (2008). Integrating waste and renewable energy to reduce the carbon footprint of locally integrated energy sectors. Energy, 33, 1489–1497. Raissi K. (1994). Total site integration. PhD thesis. Manchester, UK: UMIST. Salisbury, J. K. (1942). The steam-turbine regenerative cycle – An analytical approach. Transactions of the ASME, 64(4), 231. Varbanov, P. S., Fodor, Z., & Klemeˇs, J. J. (2012). Total site targeting with process specific Tmin . Energy, 44(1), 20–28. Varbanov, P., & Klemeˇs, J. (2011). Integration and management of renewables into total sites with variable supply and demand. Computers and Chemical Engineering, 35(9), 1815–1826. Varbanov, P., Perry, S., Makwana, Y., Zhu, X. X., & Smith, R. (2004). Top-level analysis of site utility systems. Chemical Engineering Research and Design, 82(A6), 784–795. Wan Alwi, S. R., Liew, P. Y., Varbanov, P. S., Manan, Z. A., & Klemeˇs, J. J. (2012). A numerical tool for integrating renewables into total sites with variable supplies and demands. Computer Aided Chemical Engineering, 30, 1347–1351. Zhou, Z., Liu, P., Li, Z., Pistikopoulos, E. N., & Georgiadis, M. C. (2013). Impacts of equipment off-design characteristics on the optimal design and operation of combined cooling, heating and power systems. Computers and Chemical Engineering, 48, 40–47.
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Contents lists available at SciVerse ScienceDirect
Computers and Chemical Engineering journal homepage: www.elsevier.com/locate/compchemeng
Centralised utility system planning for a Total Site Heat Integration network Peng Yen Liew a , Sharifah Rafidah Wan Alwi a,∗ , Petar Sabev Varbanov b , Zainuddin Abdul Manan a , Jiˇrí Jaromír Klemeˇs b a
Process Systems Engineering Centre (PROSPECT), Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia ˝ Centre for Process Integration and Intensification – CPI2 , Research Institute of Chemical and Process Engineering – MUKKI, Faculty of IT, University of Pannonia, Egyetemu. 10, H-8200 Veszprém, Hungary b
a r t i c l e
i n f o
Article history: Received 22 September 2012 Received in revised form 6 February 2013 Accepted 13 February 2013 Available online xxx Keywords: Total Site Heat Integration Pinch Analysis Total Site Sensitivity Table Sensitivity analysis Utility production planning
a b s t r a c t Total Site Heat Integration (TSHI) is a technique of exchanging heat among multiple processes via a centralised utility system. An analysis of the integrated multiple processes, also known as the Total Site (TS) system sensitivity, is needed to characterise the effects of a plant maintenance shutdown, to determine the operational changes needed for the utility production and to plan mitigation actions. This paper presents an improved Total Site Sensitivity Table (TSST) to be used as a systematic tool for this purpose. The TSST can be used to consider various ‘what if’ scenarios. This tool can be used to determine the optimum size of a utility generation system, to design the backup generators and piping needed in the system and to assess the external utilities that might need to be bought and stored. The methodology is demonstrated by using an Illustrated Case Study consisting of three processes. During the TS normal operation, the Total Site Problem Table Algorithm (TS-PTA) shows that the system requires 1065 kW of High Pressure Steam and 645.5 kW of Medium Pressure Steam as the heating utility, while for the cooling utility, 553.5 kW of Low Pressure Steam and 3085 kW of cooling water are required. The results of the modified TSST proposed that a boiler and a cooling tower with the system design requiring a maximum capacity of 2.172 MW of steam and 4.1865 MW of cooling water are needed to ensure an operational flexibility between the three integrated processes. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Beginning in the 1970s, research on maximising heat recovery using the Pinch Analysis technique has grown rapidly. Building upon the analysis designed for a single plant heat recovery system, previous works have also explored the potential of integrating the heat requirements for multiple plants via a centralised utility system, further reducing the utility requirements in industry and producing integrated community systems. This analysis is known as the Total Site Heat Integration (TSHI). The TSHI concept was first introduced by Dhole and Linnhoff (1993). This integration method offers a greater energy savings opportunity compared with the focus on the single processes. The Site Sink-Source Profiles (SSSP) are composite profiles derived from the combined Grand Composite Curves (GCCs) of the individual processes. SSSP could be divided into site source and sink profile. The site source profile is the total energy available in all processes, while the site sink profile shows
∗ Corresponding author. Tel.: +60 07 5535533; fax: +60 07 5581463. E-mail addresses: [email protected], sr [email protected] (S.R. Wan Alwi).
the total energy requirement in the processes. These profiles were introduced by Dhole and Linnhoff (1993) and Raissi (1994) to target the overall energy requirements for the Total Site system. Klemeˇs, Dhole, Raissi, Perry, and Puigjaner (1997) extended the targeting method to include the Total Site Profile (TSP), the Site Composite Curves (SCC) and the Site Utility Grand Composite Curve (SUGCC). For the same concept, the TSP is synonymous with a SSSP, while the SCC are constructed by performing Multiple Utility (MU) targets on the TSP. The SUGCC is a form of the site composite, providing valuable insights on the cogeneration potential for the Total Site (TS). These tools have significantly impacted the development of the TSHI technique. To reduce the carbon footprint, Perry, Klemeˇs, and Bulatov (2008) have conceptually extended the TSHI by integrating large community servicing with corporate buildings as additional heat sinks and renewable energy as heat sources. The inherent variability in the heat supply and demand increased the difficulty in both handling and controlling the system. Varbanov and Klemeˇs (2011) later introduced into the Total Site description the Time Slices with a heat storage system for handling the variable supply and demand in the TSHI using the heat integration of the individual batch processes. In the same paper, the Total Site Heat
0098-1354/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.compchemeng.2013.02.007
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Nomenclature TS TT T T CHP CW GCC HPS LIES LPS mCp MU MU-PTA PTA Qcmin Qhmin SCC SDN SUGCC SSSP TS TSP TSHI TSST TSUD TS-HSC TS-PTA DH Tmin,pp Tmin,up
initial supply temperature (◦ C) final target temperature (◦ C) shifted temperature (◦ C) double-shifted temperature (◦ C) Combined Heat and Power cooling water Grand Composite Curve high-pressure steam Locally Integrated Energy Sector low-pressure steam heat capacity flowrate (kW/◦ C) multiple utility Multiple Utility Problem Table Algorithm Problem Table Algorithm minimum cooling requirement (kW) minimum heating requirement (kW) Site Composite Curve Steam Distribution Network Site Utility Grand Composite Curve Site Sink-Source Profile Total Site Total Site Profile Total Site Heat Integration Total Site Sensitivity Table Total Site Utility Distribution Total Site Heat Storage Cascade Total Site Problem Table Algorithm Stream Heat Load (kW) minimum temperature difference between process stream (◦ C) minimum temperature difference between utility and process streams (◦ C)
Cascade was introduced for visualising the heat flows across processes, the steam system and the heat storage system. Wan Alwi, Liew, Varbanov, Manan, and Klemeˇs (2012) introduced a numerical solution for the TSHI system to address the variable availability. This work presented a Total Site Heat Storage Cascade (TS-HSC) to address the heat storage facilities required by the TS system. Nemet, Klemeˇs, Varbanov, and Kravanja (2012) discussed the approaches needed to maximise the use of the renewable energy sources with a fluctuating supply. They introduced a framework for the integration of the chemical processes with solar energy, allowing a user to determine the amount of potential solar thermal energy that could be used within a process. Varbanov, Fodor, and Klemeˇs (2012) revisited the global minimum temperature difference (Tmin ) used in the previous method. This work suggested that the values for Tmin should be specified for each process on the site individually. They demonstrated that the assumption of a global Tmin for the entire Total Site may have been oversimplified, leading to inadequate results with the imprecise estimation of the overall Total Site heat recovery targets. The modified Total Site targeting procedure proposed in the paper allowed for more realistic heat recovery targets for the Total Sites to be targeted. A graphical approach was used in the early stages of the TS targeting, including the TSP, the SCC, the SUGCC construction (Klemeˇs et al., 1997), the TS targeting methodology for both industrial processes and renewable energy sources (Perry et al., 2008) and the TS targeting methodology with both process and utility specific Tmin (Varbanov et al., 2012). Liew, Wan Alwi, Varbanov, Manan, and Klemeˇs (2012) recently introduced an alternative approach
based on a numerical method known as the Total Site Problem Table Algorithm (TS-PTA) to target the Total Site utility requirement. This method is easier to construct, giving faster and more accurate results compared to the graphical approach, which has a tendency to include a graphical error with the curve shifting. The Total Site Utility Distribution (TSUD) Table was also introduced to visualise the heat flows between the processes and the utility system. A numerical tool, the Total Site Sensitivity Table (TSST), to explore the site sensitivity was also proposed in the same paper. There are several mathematical models for the plant utility system planning process that incorporate the TSHI theory. Mavromatis and Kokossis (1998) introduced models for a steam system in the TSHI with two main objectives, the selection of the pressure steam levels and the determination of the operating unit configuration for the steam levels. A new methodology was developed by Halasz, Nagy, Ivicz, Friedler, and Fan (2002) for the optimal retrofit synthesis and operation of the steam-supply system of a chemical complex with production capacities for a multitude of products that vary temporarily. Marechal and Kalitventzeff (2003) proposed optimisation models for solving a multi-period problem that incorporated the selection and target for the optimum operational strategy for a utility system. A top-level analysis (Varbanov, Perry, Makwana, Zhu, & Smith, 2004) is another mathematical modelling methodology that can be used for these concepts. This method allows for “scoping”, i.e., selecting the site processes to target for the heat integration improvements. The current steam and power demands can be optimised and the potential benefit of reducing the steam demand can be assessed. A set of curves for the steam marginal prices can be produced for the system under consideration via a top-level analysis. Chen and Lin (2011) proposed a systematic optimisation approach to design a Steam Distribution Network (SDN) of the steam systems to obtain an improved energy utilisation in the network. In this model, the operating conditions of the SDN were treated as design variables to be optimised. In another development on the TSHI, Bandyopadhyay, Varghese, and Bansal (2010) proposed a simplified methodology to target the cogeneration potential based on the Salisbury (1942) approximation. This method is simple and linear, using the rigorous energy balance at the steam header. Kapil, Bulatov, Smith, and Kim (2012)introduced a new model based on an isentropic expansion. These model results were favourable compared with the results from the detailed isentropic design methods. This method also included an optimisation study, which systematically determined the levels of the steam mains, subjected to economic parameters and constraints. The TSST was first proposed by Liew et al. (2012). The tool could be used to systematically determine the minimum and maximum boiler and cooling utility capacities at different operating conditions. However, the tool has a major assumption, which treated the hot utility and the cold utility as the same type of utility. For example, the “Difference from normal operation” should not be calculated for the scenario when the Low Pressure Steam (LPS) consumption for the base case are located at different Pinch regions. This is because the steam generated cannot be used to satisfy the cooling requirement at the same steam level. Furthermore, the tool can be further developed to explore the potential of cascading the excess energy at high temperature to satisfy the LPS requirement during the process operational change scenario. In the method proposed previously, the maximum and minimum boiler capacities are also not determined in a systematic way via the TSST. The potential worst case scenario was also not identified as there was no specific ways to determine the numbers of “what if” scenarios. In this paper, the limitations faced by the TSST methodology introduced by Liew et al. (2012) is addressed and the tool is improved to include the insights and guidelines generated from the
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TSHI utility production system planning process. This tool is able to determine the worst case scenario, the maximum capacity and the turn-down ratio for each type of utility supply for multiple scenarios. This approach also allows for a more flexible plant operation with a low Total Site sensitivity towards operational disturbances. The effects of a process disruption within a Total Site can be analysed with this tool to allow contingency plans and actions to be taken to avoid disruptions in the other processes that are integrated in the system. The process disruptions may include shutdowns of one or more plants, a scheduled maintenance, production changes or emergency cases. 2. Methodology The proposed methodology for the improved Total Site Sensitivity Table (TSST) is defined in the following steps. 2.1. Step 1: stream data determination The hot and cold stream data for the individual plants that would be integrated in the Total Site system are determined. This process includes the supply and target temperature data, the fluid flow rate and the heat capacity data, information that is essential for a Pinch Analysis study. The existing utility temperature levels from the centralised utility system are also determined. 2.2. Step 2: TS utility requirement determination Once the data are determined, the Total Site Heat Integration analysis can be performed by using either the established graphical or the numerical approach. The TSHI analysis involves the targeting of the individual plant heat recovery potential and the determination of the loads and levels of utilities that can be generated below the Pinch region (as TS heat sources) and used to satisfy the heat requirements (TS sinks) above the Pinch region. The determination of the steam requirements for these multiple utility levels can be obtained by using either the Grand Composite Curves (GCC) with the Total Site Profile (TSP) introduced by Klemeˇs et al. (1997) or the Multiple Utilities Problem Table Algorithm (MU-PTA) by Liew et al. (2012). The optimum utility levels are determined by varying the steam saturation temperature or pressure on the established tools. These TS sources and sinks streams are then composited and the TS minimum multiple utility target after the TS heat recovery can be determined using either the Site Composite Curve (SCC) with the Site Utility Grand Composite Curve (SUGCC) (Klemeˇs et al., 1997) or by a numerical approach through the Total Site Problem Table Algorithm (TS-PTA) (Liew et al., 2012). 2.3. Step 3: Total Site Sensitivity Table (TSST) construction The TSST is a useful tool, demonstrating the effect of plant shutdowns or operability on the TS utility generation and requirements. The following methodology components can be used to construct the improved sensitivity analysis tool. 2.3.1. Determining the numbers of possible scenarios The possible scenarios for a shutdown for either a single plant or multiple plants can be estimated using Eq. (1). This equation can accurately determine the number of scenarios (Sn ) needed to be examined in the TSST as a function of the number of plants (n) integrated in the TS. In this equation, the effect of a total plant shutdown is assumed to be the consequences derived from the worst case scenario. As an example, for three integrated plants, Plants A, B and C, the seven potential scenarios in the TS analysis would be:
3
Scenario 1: All plants in full operation (base case) Scenario 2: Plant A shutdown, Plants B and C in operation Scenario 3: Plant B shutdown, Plants A and C in operation Scenario 4: Plant C shutdown, Plants A and B in operation Scenario 5: Plants A and B shutdown, Plant C in operation Scenario 6: Plants A and C shutdown, Plant B in operation Scenario 7: Plants B and C shutdown, Plant A in operation Sn =
1 3 5 n + n n = 2, 3, 4, 5 . . . 6 6
(1)
where S, number of scenarios; n, number of plants/processes. 2.3.2. Obtaining the TS targets for all possible scenarios Step 2 is repeated to obtain the utility requirement for the Total Site system for the possible scenarios. To do this, the source and the demand data of the plant being shut down are omitted in the construction of the TSP or the TS-PTA. 2.3.3. Recording the TS target at utility levels with storage facilities The requirements for the different types of utilities during the different scenarios are recorded in the TSST. The value for the hot utility (MU above the TS Pinch point) is recorded without bracket, while the value for the cold utility (MU below the TS Pinch Point) is recorded in a square bracket to emphasise the differences. The location of the TS Pinch Point is also noted. 2.3.4. Determining the requirement difference of base case and each scenario Next, the effect of the variations between the base case with all plants operating normally and the various possible scenarios for the TS centralised utility system needs to be analysed. For the cases in which the multiple utility for the base case and the Scenario i is located in the same Pinch region (either both above the Pinch or both below the Pinch), the difference between the Scenario i and the base case utility can be calculated using Eq. (2) for each utility type j: MUDifference,j = MUbase−case,j − MUSi,j
(2)
where MUDifference,j , multiple utility variations between the base case and the scenario for the Utility j; MUbase-case,j , multiple utility of the base case for the Utility j; MUSi,j , multiple utility of the Scenario i for the Utility j. A positive difference indicates that there is an excess utility produced by the boiler houses or the chilling units compared with the base case scenario, while a negative difference represents a deficit in the external utility. For scenarios where the MUbase-case,j and the MUSi,j are located at different Pinch regions, the utility was changed from a hot to a cold utility requirement or vice versa. For example, for the MUbase-case,j located above the Pinch, this situation would require a Low Pressure Steam (LPS) as the hot utility. With the MUSi,j located below the Pinch, the situation does not require a LPS, but rather generates a LPS that will require the stream to be cooled down with cooling water. This scenario indicates that the centralised utility system will have an excess LPS from the boiler during Scenario i, generating an LPS from the process without a reduction in the boiler capacity. This situation would result in a double cooling utility needed during Scenario i. A summary of the Scenario analysis is as follows: (i) If the MUbase-case,j is located above the Pinch and the MUSi,j is located below the Pinch, more cold utility will be required. The calculation of the difference is required to determine both the heating and the cooling utility. For the heating utility, MUDifference,j = −MUbase−case,j
(3)
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Table 1 Stream data for Processes A, B and C.
For the cooling utility MUDifference,j = MUSi,j
(4)
(ii) If the MUbase-case,j is located below the Pinch and the MUSi,j is located above the Pinch, the cold utility produced is not needed, but extra steam for heating is required in this scenario. Eq. (4) can be used to determine the difference of the heating utility, while the difference for the cooling utility could be determined by Eq. (3). 2.3.5. Obtaining the difference after cascade The third step in the TSST is to calculate the “difference after cascade”. For the hot utility, the excess is kept at the highest level with the deficit at the lowest level. For the cold utility, the deficit is kept at the lowest temperature with the excess at the original utility level. This value could be determined using the heuristic below:
Stream Process A A1 hot A2 hot A3 cold A4 hot Process B B1 hot B2 hot B3 cold B4 cold Process C C1 hot C2 cold C3 cold C4 cold
TS (◦ C)
TT (◦ C)
H (kW)
mCp (kW/◦ C)
T S (◦ C)
TT (◦ C)
200 150 50 170
100 60 220 150
2000 3600 −2550 1000
20 40 15 50
190 140 60 160
90 50 230 140
200 200 30 130
50 119 200 150
450 1863 −680 −300
3 23 4 15
190 190 40 140
40 109 210 160
240 50 40 109
100 250 190 140
210 −400 −1500 −186
1.5 2 10 6
230 60 50 119
90 260 200 150
3.1. Step 1: steam data extraction • For an excess utility (positive MUDifference,j ) above the TS Pinch location in a scenario, this value is cascaded down to the lower utility level with a heating utility deficit (negative difference) to form the “difference after cascade”. As the higher hot utility levels (e.g., HPS) are typically more expensive than the lower hot utility levels (e.g., MPS), the lower temperature hot utilities are preferred to be cascaded downward to the heating utility deficit, ensuring that the production of the higher temperature utility can be reduced to reduce operating costs. For a heating utility in excess of 200 kW of HPS and 100 kW of MPS, a value of 200 kW for the LPS would be insufficient in this case. The total of 300 kW of the higher utility level could be let down to the LPS level, but with only 100 kW of the MPS and the HPS available to be let down to the LPS level. The net utility excess of 100 kW could remain in the HPS to ensure that this high quality heat could be sold or the heating utility generation can be reduced. • For the scenarios below the TS Pinch region, the deficit of the cooling utility (the negative difference in brackets) for the steam generation can be cascaded downwards to the cooling water level as there is no need to generate steam without a requirement. The generation of the unused steam would only require an additional boiler capacity with the excess heat being removed with cooling water. 2.3.6. Determining the storage capacity required The capacity requirements for the centralised utility system can be summarised using the results from each scenario: • The maximum requirement for each type of utility can be calculated by adding the absolute value of the most negative number in the “difference after cascade” with the utility requirement at normal operating conditions. With no negative values, the maximum utility requirement would be equal to the normal operation utility. • The minimum steam utility requirement for each type of utility can be calculated by deducting the most positive value of the “difference after cascade” from the utility requirement at normal operating conditions. The utility requirement during normal operations would be used for the cases without a positive difference.
3. Case study The construction of the Total Site Sensitivity Table (TSST) is illustrated using a case study.
The Illustrative Case Study consisted of three process units, Processes A, B, and C, as shown in Table 1. The minimum temperature difference between the process streams (Tmin,pp ) and the minimum temperature difference between the process streams and the utility (Tmin,up ) were assumed to be 20 ◦ C and 10 ◦ C, respectively. The existing available on site utilities were High Pressure Steam (HPS) at 270 ◦ C, Medium Pressure Steam (MPS) at 180 ◦ C, Low Pressure Steam (LPS) at 133 ◦ C and cooling water (CW) at 15–20 ◦ C. The simplified utility system configuration is presented in Fig. 1. A natural gas fuelled boiler was used to produce the HPS to satisfy the site steam demand. The reduction of the steam production from the boiler would directly contribute to the carbon emission reduction of the site. Steam can also be produced from the removal of heat from the high temperature process stream. For example, the oil and gas processing industries typically employ very high temperature processes, generating both HPS and MPS at the processing site. The HPS produced from the boiler house or the processes could be stepped down to a lower energy level through a turndown valve or a steam turbine. Industries with excessive amounts of high temperature heat have frequently used steam turbines in their steam systems to generate electricity. The condensate from the used steam can be sent back to a de-aeration tank to eliminate dissolved oxygen to prevent corrosion. 3.2. Step 2: TS utility requirement determination In the next step, the Multiple Utility Problem Table Algorithm (MU-PTA) by Liew et al. (2012) was used to target the external multiple utility requirements for each individual process. Table 2 shows a sample MU-PTA for Process A. Process A had the potential to generate 50 kW MPS and 1515 kW LPS, requiring 3085 kW of cooling water. This information can be used to contribute to the
Boiler Houses HPS MPS LPS CW
De-aerator
Process A
Process B
Process C
Fig. 1. Total Site with a centralised utility system (after Klemeˇs et al., 2010).
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Table 2 MU-PTA for Process A.
mCp (kW/oC)
T’
T”
ΔT
(oC)
(oC) 270
(oC)
230
230
190 190
190 190 180
160
160
140
140 133
90
90
60
60
50
50
20
20
20
40
15
mCp
50
(kW/oC) (kW)
0
0
0
40
-15
-600
10
5
50
20
5
100
20
55
1100
7
45
315
43
45
1935
30
25
750
10
40
400
30
0
0
Table 3 Summary of multiple utility targets for each process in the Total Site.
Process HPS MPS LPS CW
Below Pinch (heat source) [kW]
Above Pinch (heat sink) [kW]
A
A
B
C
600
180 100
285 595.5 995.5
50 1515 3085
B
C
34
Initial Cascade (kW) 0
ΔH
MU Cascade (kW) 0
600
0
0 0
0 0
50
0
150
0
1250
0
1565
0
3500
0
4250
0
4650
0
4650
0
Utility Requirement (kW) HPS 600
600 PINCH -50 MPS
50
LPS
1515
CW
3085
-100 -1100 -315 -1935 -750 -400 0
The TS-PTA method by Liew et al. (2012) was used to target the Total Site multiple utility. Table 4 shows the TS-PTA for the base case scenario. In order to illustrate the utility consumption and generation, TSP and SCC are plotted based on the TS-PTA (Table 4). Fig. 2 shows the TSP and SCC for the Illustrative Case Study. The TS Pinch point was located between the LPS and the CW. A multiple utility targeting on the TS-PTA demonstrated that the system required 1065 kW of HPS and 645.5 kW of MPS as the heating utility for the entire TS. For the cooling utility, 553.5 kW of LPS and 3085 kW of CW was required. The SDN for the integrated TS system in the Illustrative Case Study is shown in Table 5, the Total Site Utility Distribution (TSUD) Table. These values were recorded in the second column of the TSST as shown in Table 6.
TS heat sources. Process A also required 600 kW of HPS for heating, representing the TS heat sinks. MU-PTA was also performed for Processes B and C. Table 3 summarises the multiple utility targets for each process.
Table 4 Total Site Problem Table Algorithm (TS-PTA) for the Illustrative Case Study on normal operation. 1 Utility
2 Heat source (kW)
HPS MPS
50
3 Heat sink (kW)
4 Heat requirement (kW)
1065
−1065
695.5
5 Initial cascade (kW)
6 Final cascade (kW)
7 MU cascade (kW)
0
1710.5
0
−1065
645.5
0
0
0
−1157
553.5
0
1928
3638.5
0
1065
−645.5 −1710.5
LPS
1549
CW
3085
995.5
8 Utility requirement (kW)
645.5 TS Pinch −553.5
553.5
−3085
3085
Table 5 Total Site Utility Distribution (TSUD) Table for the Illustrative Case Study.
Process A
Heat Source [kW] Process Process B C
HPS MPS
50
LPS
1,515
CW
3,085
Site Utility
Process A
1,065
600
645.5 34
Heat Sink [kW] Process Process B C 180
285
100
595.5 995.5
Site Utility
553.5 3,085
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Scenario 2 (Processes B and C in operation)
Scenario 3 (Processes A and C in operation)
Scenario 4 (Processes A and B in operation)
Utility
Requirement (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
Requirement (kW)
Difference (kW)
Difference after cascade (kW)
1065
465
600
0
885
180
180
780
285
285
645.5 Pinch
695.5
−50
0
545.5 Pinch
100
100
50 Pinch
595.5
595.5
961.5
−961.5 [553.5]
−411.5 [553.5]
[519.5]
[34]
[34]
[1549]
[−995.5]
[0]
[3085]
[3085]
[3085]
[0]
[0]
[3085]
[0]
[−995.5]
(a) HPS MPS LPS
[553.5] CW
Pinch [0]
[3085]
Scenario 1 (all processes in operation – base case)
Scenario 5 (Process A in operation)
Scenario 6 (Process B in operation)
Scenario 7 (Process C in operation)
Summary
Utility
Requirement
Requirement
Difference
Difference after cascade
Requirement
Difference
Difference after cascade
Requirement
Difference
Difference after cascade
Maximum requirement
Minimum requirement
(b) HPS
1065
600 Pinch
465
99
180
885
885
285
780
0
1065
180
MPS
645.5
645.5 [−50]
645.5 [0]
100
545.5
545.5
595.5
50
0
695.5 [0]
0 [0]
995.5
−995.5 [553.5]
−165.5 [553.5]
411.5 [553.5]
0 [0]
[3085]
[3085]
[4186.5]
[0]
[50] Pinch
Pinch
LPS
CW
[553.5]
[1515]
[−961.5]
[0]
[34]
[519.5]
[519.5]
[3085]
[3085]
[0]
[−1011.5]
[0]
[3085]
[3085]
Pinch [0]
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Scenario 1 (all processes in operation – base case)
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Table 6 Total Site Sensitivity Table (TSST).
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HPS 250
200
MPS
150
Site Source Profile
LPS Site Sink Profile
100
50
CW
0
-6000
-5000
-4000
-3000
-2000
-1000
0
1000
2000
3000
4000
Fig. 2. Total Site Profile (TSP) and Site Composite Curves (SCC) for the Illustrative Case Study.
3.3. Step 3: Total Site Sensitivity Table (TSST) construction For the three processes involved in this Illustrative Case Study, the number of possible scenarios involving process shut downs is equal to seven, as suggested by Eq. (1). The TS-PTAs for each scenario were constructed. The multiple utility targets with the TS Pinch location are listed in Table 6. The differences between the normal operating conditions and the various scenarios of the TS utilities requirement are determined based on above or below TS Pinch location, by using Eqs. (2)–(4) (as explained in Section 2.3). This step is corrected from the difference calculation without considering the location of TS Pinch in the previous published methodology in Liew et al. (2012). For example, the TS Pinch location changed from a point between the MPS and the LPS for the base case to a point between the LPS and the CW for Scenario 2. The difference between the base case and Scenario 2 for the HPS, the MPS and the CW can be calculated directly using Eq. (2), as these values are located in the same Pinch region. These values are given in Column 4, Table 6a. The positive difference indicated that the boiler was producing an excess of 600 kW of the HPS and the cooling tower had an excess of 3850 kW of the CW that was not used during Scenario 2. The negative difference indicated there was a deficit of 50 kW of MPS that was needed to be generated. For the LPS, the utility location changed from below the Pinch (base case) to above the Pinch (Scenario 2). The previous methodology by Liew et al. (2012) is expected to yield 408 kW of extra LPS requirement in Scenario 2. However, the extended TSST in this paper indicates that the system requires an additional boiler to generate the LPS instead. The negative difference indicated a deficit of 961.5 kW in the LPS. The additional CW was added at the CW difference row. The “difference after cascade” was calculated for each of the scenarios. The excess heating utility, which is represented by a positive difference, can be cascaded towards the lower steam utility level characterised by a negative difference for the point above the Pinch region. This type of heat recovery is not included in the previous published TSST (Liew et al., 2012) methodology. In Scenario 2, Process A can be shut down due to a scheduled maintenance. This shutdown would not need the 600 kW HPS generated from the centralised utility system for Process A during the base case, while increased levels of the MPS and the LPS would be needed to satisfy the requirements for Processes B and C. To minimise the changes in the boiler utility generation, the excess unused HPS (indicated by a positive difference) can be cascaded downwards to satisfy the deficits in the MPS and the LPS. This cascade would allow the HPS and the MPS boiler to run as usual, with only an additional
7
411.5 kW LPS needed to be generated. For the points below the Pinch region, there is only one utility type (CW) in excess, indicating that the 3085 kW CW production would need to be shutdown during Scenario 2. After analysing the various ‘what if’ scenarios in the TSST, the TS system in this demonstration case study required a natural gas powered boiler with a maximum capacity of 2172 kW of superheated HPS production. The superheated steam generated with this system could be stepped down to 1065 kW of HPS, 695.5 kW of MPS and 411.5 kW of LPS, compared with the 1710 kW of total steam required during normal operations. A backup boiler may be a good option to cater to these production changes or the steam requirement may also be obtained externally. In the most extreme case, the minimum total steam requirement for the TS system was 180 kW during Scenario 6, as shown in Table 6b. For instance, the boiler in the TS required a turn down ratio of not less than 50%, assuming the lowest capacity of the boiler to be 1086 kW. These conditions would suggest that the remaining 906 kW of steam needed to be cooled down using cooling water or sold to other plants. Another alternative would be to divert the excess steam production for the Combined Heat and Power (CHP) system to generate more power. Another choice could also include dividing the capacity between two boilers, allowing the boiler capacity to be manipulated based on the equipment restrictions. For the cooling water, the maximum capacity required was 5092.5 kW. An additional 4186.5 kW for the maximum capacity and 906 kW of steam generated was required due to the limitations from boiler’s turn down ratio. The minimum capacity for the cooling tower was 0 kW. 4. Conclusion The Total Site Sensitivity Table (TSST) has been extended for planning the TSHI centralised utility system. This approach provides insights on the consequences of a plant shutdown or process upsets on the entire TS system integration and the centralised utility system. By identifying heating or cooling utility requirements during a plant shut down, a suitable size utility system can be planned to ensure a flexible and undisrupted operation for the integrated processes. These decisions must be balanced with the operational challenges as well as the capital and operating costs. The proposed tool is able to determine the optimal design and operation of the centralised utility system by assuming 100% efficiency for the utility system. This is actually not representing the actual situation. For the future work, the effect of load changes on the TS utility system efficiencies can be further investigated. For example, the turbine and boiler efficiencies are affected by their loads (Möller, Genrup, & Assadi, 2007; Zhou, Liu, Li, Pistikopoulos, & Georgiadis, 2013). Hence, the off-design operation may require special considerations during the utility system sizing. Acknowledgements The authors would like to thank the Ministry of Higher Education (MOHE) Malaysia and the UTM in providing the research funding for this project under Vote No. Q.J130000.2544.03H44 and the EC supported project Energy – 2011-8-1 Efficient Energy Integrated Solutions for Manufacturing Industries (EFENIS) – ENER/FP7/296003/EFENIS. References Bandyopadhyay, S., Varghese, J., & Bansal, V. (2010). Targeting for cogeneration potential through total site integration. Applied Thermal Engineering, 30, 6–14. Chen, C., & Lin, C. (2011). A flexible structural and operational design of steam systems. Applied Thermal Engineering, 31, 2084–2093.
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