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Performance Assessment and Benchmarking of Desalination Plants
I.A. Karimi and Rajagopalan Srinivasan (Editors), Proceedings of the 11th International Symposium on Process Systems Engineering, 15-19 July 2012, Singapore. © 2012 Elsevier B.V. All rights reserved.
Performance Assessment and Benchmarking of Desalination Plants N. Bhutani,a M. Srinivas,a Senthilmurugan S.,b a
ABB Corporate Research, Bangalore, Karnataka, India ABB Water ISI, Bangalore, Karnataka, India
b
Abstract ABB has developed a generic “technology” based tool for Energy Assessment and Benchmarking of desalination plants. It facilitates systematic and quick opportunity identification of energy efficiency improvements along with cost-benefit estimation in typical Multi-Stage Flash (MSF) and Reverse Osmosis (RO) based desalination Plants. The tool (i) calculates energy flow distribution, efficiency, losses in equipments and various performance indices (ii) recommends measures/proposals to improve efficiency based on energy assessment and key performance indices (KPIs) based benchmarking (iii) recommends proposals with cost-benefit analysis and (iv) generates energy assessment report. As a test bed, the energy assessment study performed on MSF desalination plant with this tool is presented. Keywords: Energy efficiency, energy assessment, desalination, reverse osmosis, multistage flash, cost-benefit estimation
1. Introduction Desalination plants play an important role in producing potable water. Multi stage flash (MSF) and reverse osmosis (RO) desalination plants are two pre-dominant seawater desalting systems in the world, constituting more than half of the total desalination capacity. These plants present major opportunities to improve energy efficiency, plant production and profitability [1]. Many authors have applied concept of exergy analysis [2-4] to assess various industrial processes [5-7] but the industrial application of these concepts for energy assessment and benchmarking is very limited. To overcome above limitations, a generic, ‘technology’ based, graphic user interface (GUI) enabled tool for “performance assessment and benchmarking” of desalination systems is developed.
2. Energy Assessment and Benchmarking - Methodology Conventionally, the energy assessment for industrial processes is performed by domain experts, based on their experience, by – recording, analysis, benchmarking, targeting, and reporting and control respectively. This onsite energy assessment exercise is quite tedious, prone to human errors and sometimes lacks thorough analysis. However, by means of automated energy assessment tool the overall procedure for energy assessment is simplified to these key functionalities: (i) Exergy analysis (ii) KPI calculations (iii) Cost-benefit estimation, explained by means of an application on MSF plant.
3. MSF Desalination Plant 3.1. Process The schematic flow diagram of an MSF desalination process is shown in Figure 1. The system consists of Heat recovery section (HrecS), Heat reject section (HrejS), a brine
Performance Assessment and Benchmarking of Desalination Plants
1101
heater, vacuum system, and couple of pumps. The HrecS and HrejS consists 19 and 3 flashing units respectively. The seawater enters the condenser tubes of HrejS where its temperature is raised by absorption of the latent heat of the condensing water vapor on other side of tubes. Partly, the sea water is rejected back to the sea and the rest makes feed, which is chemically treated and then mixed to the brine pool of the last flashing stage of HrejS. The brine, partly extracted from HrejS, is introduced to HrecS (condenser tubes) where it first absorbs latent heat of condensing vapors, and then of the steam in brine heater. The heated brine is then introduced to HrecS first stage where it flashes off, in the subsequent flash columns and gets condensed to form the distillate product stream, which is extracted from the last stage of HrejS. The main thermal energy input to MSF results from use of LP steam in brine heater. Partly, excess steam is vented off or sent to dump condenser (if existing) for steam condensate recovery. MP steam, in small quantity compared to LP steam, is used in vacuum system (not shown in diagram) to remove non-condensable from Flash column. The electricity is consumed to run pumps for Sea water (SW) supply, brine recirculation (R/C pump), distillate product, condensate return (Cond pump) and brine blowdown (B/D pump) etc.
Figure 1 Simplified Process Flow Diagram for MSF desalination Plant
4. Case Study Results As a pilot case study, the above industrial MSF desalination plant configuration was analyzed using this tool. The steady state operating data collected from the plant for a year of operation was preprocessed by data preprocessor and used for energy assessment in following steps. 4.1. Exergy Analysis By exergy analysis, it was found that energy was mainly consumed in useful work, destroyed due to inefficiency (of mechanical or thermal process type) in process equipments like heat exchangers, pumps, flash stages, desuperheater or lost to environment with boundary streams (like brine blowdown, sea water reject) etc. The average distribution of exergy destruction in various equipments in the MSF desalination plant (Figure 2) reveals that almost 57% of the thermal energy is destroyed in MSF stages due to irreversible throttling and expansion in multiple flash stages,
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followed by 20.7 % energy loss in desuperheater (D/S) due to mixing of superheated steam with condensate spray and 12.1 % loss in brine heater due to inefficiency. On an average 4 % of the energy is lost due to dumping of steam to dump condensers. Though the condensate is fully recovered from dump condensers, the latent heat of steam is still lost in the process. About 2.8 % of energy, in the form of electrical energy, is lost due to inefficiency of brine recirculation pumps. It is found that brine recirculation pump is the biggest pump in MSF desalination section and consumes more than 80% of total electrical input power to MSF section. About 1.8 % of the total energy is lost due to throttling in brine recirculation valve. Energy destruction in other equipments (like brine blowdown pump, distillate pump, condensate pumps etc) and direct losses to environment with brine blowdown stream, distillate product delivery, etc were negligible and therefore combined together into “Others” which makes 1.5 % of the total energy destruction/loss.
2.8%
1.8% 4.0%
1.5%
Brine Heater
12.1%
Desuperheater MSF_Section
20.7%
Recirculation Pump Brine R/C Pump Valve
57.2%
Dump Condenser Others
Figure 2 Exergy destruction in MSF desalination Plant
Energy Efficiency [ - ]
Energy Efficiency [ - ]
1 0.9 0.8 0.7 Operation Best Fit
0.6 0.5 0.5
0.6
0.7
0.8
0.9
Desuperheater Steam Flow Rate, [ - ]
1
1.0 Operation Best Fit
0.9 0.8 0.7 0.6 0.5 0.5
0.6
0.7
0.8
0.9
1.0
Brine R/C Pump Flow Rate, [ - ]
Figure 3 Energy efficiency of Desuperheater (left) and brine recirculation pump (right) The dimensionless exergy efficiency of brine recirculation (R/C) pump and desuperheater are plotted in Figure 3. The exergy efficiency of desuperheater increases from 0.7 and 0.90 when the steam flow rate is increased from 0.7 to 1. Similarly, the exergy efficiency of brine recirculation pump increases from 0.8 to 1 when the flow is increased from 0.8 to 1, signifying opportunities for improvement in energy efficiency of both the equipments by increasing load on both the equipments. Also, for the fixed
Performance Assessment and Benchmarking of Desalination Plants
1103
flow conditions, the variations in efficiency are huge in case of desuperheater, signifying possible improvements in energy efficiency by reduced variations.
0.13
Operation Best Filt
0.12
0.11
0.10 0.00
0.50
1.00
Sp. Elect. Consumption, [ ]
Sp. Steam Consumption, [ ]
4.2. KPI Calculator Various KPIs, defined in the tool, were configured to plant data and calculated for MSF desalination plant configuration. Trend plots were generated for these KPIs to evaluate their impact on plant performance. The specific steam consumption and specific electricity consumption in desalination plant can be reduced by increasing load factor (Figure 4). This would result in a maximum improvement in plant profit of ~ 0.2 kUSD/h (Figure 5, left). Note that a maximum total profit of 650 kUSD/year is possible based on the current plant production distribution profile. The specific steam consumption in plant can also be reduced by reducing the losses due to excessive dumping of steam to dump condenser (Figure 5, right). The mean values of some of the KPIs, defined in Error! Reference source not found., were also compared against recommended values to identify improvements. As shown, by comparison in Error! Reference source not found., a few KPIs are operating within permissible limits while others can be improved further to improve plant performance.
1.50
3.9
Operation Best Filt
3.7 3.5 3.3 3.1 2.9 2.7 2.5 0.00
Water Production, [ ]
0.50 1.00 Water Production, [ ]
1.50
0.14 Operation Best Fit
0.13 0.12 0.11 0.10 4
5 6 7 8 9 10 % Steam to Dump Condenser, [ ]
0.25 Plant Profit, kUSD/h
Sp. Steam Consumption, [ ]
Figure 4 Specific steam consumption (left) and specific electricity consumption (right) with respect to water production.
0.20
Operation Best Fit
0.15
0.10 0.05
0.00 0.60 -0.05
0.70
0.80
0.90
1.00
1.10
Water Production, [ ]
Figure 5 % Steam consumption vs. Specific steam consumption (left) and Water production vs. Plant profit (right) in an MSF desalination Plant. 4.3. Cost-Benefit estimation In this section, the efficiency estimates of equipments from exergy analysis and improvements in KPIs were translated into cost savings. The estimated cost savings resulting from improved equipments efficiency of brine heater, desuperheater and brine
N. Bhutani et al.
1104
recirculation pump by improving load factor were 17, 21 and 30 kUSD/year, brine blowdown heat recovery was 19 kUSD and reduced steam losses by no dumping of steam to dump condenser was 104 kUSD respectively. Note that savings are tuned to current production of the pilot plant. Further, cost-benefit analysis is feasible with this tool for replacement of fixed drive with variable frequency drive (VFD) for pumps or other capital investments.
Table 1 Calculated KPI for MSF desalination Plant KPI Definition Sp. Steam Consumption in major consumers, tons/m3 water Sp. Electricity Consumption in major consumers, kWh/m3 water % Brine Blowdown, %
Mean Value Recommended 0.12 Least Possible
Distillate To Makeup Ratio, [ ] % Steam To Dump Condenser,
3.22
Least Possible
62.56
Least Possible
0.36
b/w 0.3-0.4
%
8.18
Equal to 0 or Least Possible
o
30.12
Less than equal to 10-15 oC
Degree Superheat of LP steam, C
Degree Superheat of Brine Heater steam, 10.64 o C Delta T Flash MSFSection, oC 57.20 o
Less than equal to 5 oC Highest Possible
Delta T, SeaWater (Inlet – Reject), C
7.87
Less than equal to 10 oC
Delta T BrineHeater (for Brine), oC
6.90
Less than equal to 5 oC
5. Conclusions The energy assessment and benchmarking tool was used to identify opportunities for energy efficiency improvements and translate them into potential cost savings for the pilot customer. With a user-friendly graphic user interface (GUI), a wide range of industrial desalination plants/configurations (thermal, hybrid, membrane based) can be analyzed very quickly. References [1]. Z. Elimelech M and Philip WA., The Future of sea water desalination: Energy, Technology, and the environment, Science, vol. 333, no. 6043, pp. 712-717, August 2011. [2]. Sharqawy M H., et. al., On exergy calculation of sea water with applications in desalination systems, International Journal of Thermal Science, vol. 50, pp. 187-196, 2011. [3]. Kahraman N., and Cengel Y. A., Exergy analysis of a MSF distillation plant, Energy conservation and management, vol. 46, pp. 2625-2636, 2005. [4]. Cerci Y., Exergy analysis of a reverse osmosis plant in California, Desalination, vol., 142, pp. 257-266, 2002. [5]. Macedonio F. and Drioli E., An exergy analysis of membrane desalination system. Desalination, vol. 261, pp. 293-299, 2010. [6]. Ataei A. and Yoo C., Combined pinch and exergy analysis for energy efficiency optimization in a steam power plant, International Journal of the Physical science, vol. 5(7), pp. 1110-1123, 2010. [7]. Rosen M. A. and Bulucea C. A., Using exergy to understand and improve the efficiency of Electrical power technologies, Entropy, vol. 11, pp. 820-835, 2009.
Performance Assessment and Benchmarking of Desalination Plants N. Bhutani,a M. Srinivas,a Senthilmurugan S.,b a
ABB Corporate Research, Bangalore, Karnataka, India ABB Water ISI, Bangalore, Karnataka, India
b
Abstract ABB has developed a generic “technology” based tool for Energy Assessment and Benchmarking of desalination plants. It facilitates systematic and quick opportunity identification of energy efficiency improvements along with cost-benefit estimation in typical Multi-Stage Flash (MSF) and Reverse Osmosis (RO) based desalination Plants. The tool (i) calculates energy flow distribution, efficiency, losses in equipments and various performance indices (ii) recommends measures/proposals to improve efficiency based on energy assessment and key performance indices (KPIs) based benchmarking (iii) recommends proposals with cost-benefit analysis and (iv) generates energy assessment report. As a test bed, the energy assessment study performed on MSF desalination plant with this tool is presented. Keywords: Energy efficiency, energy assessment, desalination, reverse osmosis, multistage flash, cost-benefit estimation
1. Introduction Desalination plants play an important role in producing potable water. Multi stage flash (MSF) and reverse osmosis (RO) desalination plants are two pre-dominant seawater desalting systems in the world, constituting more than half of the total desalination capacity. These plants present major opportunities to improve energy efficiency, plant production and profitability [1]. Many authors have applied concept of exergy analysis [2-4] to assess various industrial processes [5-7] but the industrial application of these concepts for energy assessment and benchmarking is very limited. To overcome above limitations, a generic, ‘technology’ based, graphic user interface (GUI) enabled tool for “performance assessment and benchmarking” of desalination systems is developed.
2. Energy Assessment and Benchmarking - Methodology Conventionally, the energy assessment for industrial processes is performed by domain experts, based on their experience, by – recording, analysis, benchmarking, targeting, and reporting and control respectively. This onsite energy assessment exercise is quite tedious, prone to human errors and sometimes lacks thorough analysis. However, by means of automated energy assessment tool the overall procedure for energy assessment is simplified to these key functionalities: (i) Exergy analysis (ii) KPI calculations (iii) Cost-benefit estimation, explained by means of an application on MSF plant.
3. MSF Desalination Plant 3.1. Process The schematic flow diagram of an MSF desalination process is shown in Figure 1. The system consists of Heat recovery section (HrecS), Heat reject section (HrejS), a brine
Performance Assessment and Benchmarking of Desalination Plants
1101
heater, vacuum system, and couple of pumps. The HrecS and HrejS consists 19 and 3 flashing units respectively. The seawater enters the condenser tubes of HrejS where its temperature is raised by absorption of the latent heat of the condensing water vapor on other side of tubes. Partly, the sea water is rejected back to the sea and the rest makes feed, which is chemically treated and then mixed to the brine pool of the last flashing stage of HrejS. The brine, partly extracted from HrejS, is introduced to HrecS (condenser tubes) where it first absorbs latent heat of condensing vapors, and then of the steam in brine heater. The heated brine is then introduced to HrecS first stage where it flashes off, in the subsequent flash columns and gets condensed to form the distillate product stream, which is extracted from the last stage of HrejS. The main thermal energy input to MSF results from use of LP steam in brine heater. Partly, excess steam is vented off or sent to dump condenser (if existing) for steam condensate recovery. MP steam, in small quantity compared to LP steam, is used in vacuum system (not shown in diagram) to remove non-condensable from Flash column. The electricity is consumed to run pumps for Sea water (SW) supply, brine recirculation (R/C pump), distillate product, condensate return (Cond pump) and brine blowdown (B/D pump) etc.
Figure 1 Simplified Process Flow Diagram for MSF desalination Plant
4. Case Study Results As a pilot case study, the above industrial MSF desalination plant configuration was analyzed using this tool. The steady state operating data collected from the plant for a year of operation was preprocessed by data preprocessor and used for energy assessment in following steps. 4.1. Exergy Analysis By exergy analysis, it was found that energy was mainly consumed in useful work, destroyed due to inefficiency (of mechanical or thermal process type) in process equipments like heat exchangers, pumps, flash stages, desuperheater or lost to environment with boundary streams (like brine blowdown, sea water reject) etc. The average distribution of exergy destruction in various equipments in the MSF desalination plant (Figure 2) reveals that almost 57% of the thermal energy is destroyed in MSF stages due to irreversible throttling and expansion in multiple flash stages,
N. Bhutani et al.
1102
followed by 20.7 % energy loss in desuperheater (D/S) due to mixing of superheated steam with condensate spray and 12.1 % loss in brine heater due to inefficiency. On an average 4 % of the energy is lost due to dumping of steam to dump condensers. Though the condensate is fully recovered from dump condensers, the latent heat of steam is still lost in the process. About 2.8 % of energy, in the form of electrical energy, is lost due to inefficiency of brine recirculation pumps. It is found that brine recirculation pump is the biggest pump in MSF desalination section and consumes more than 80% of total electrical input power to MSF section. About 1.8 % of the total energy is lost due to throttling in brine recirculation valve. Energy destruction in other equipments (like brine blowdown pump, distillate pump, condensate pumps etc) and direct losses to environment with brine blowdown stream, distillate product delivery, etc were negligible and therefore combined together into “Others” which makes 1.5 % of the total energy destruction/loss.
2.8%
1.8% 4.0%
1.5%
Brine Heater
12.1%
Desuperheater MSF_Section
20.7%
Recirculation Pump Brine R/C Pump Valve
57.2%
Dump Condenser Others
Figure 2 Exergy destruction in MSF desalination Plant
Energy Efficiency [ - ]
Energy Efficiency [ - ]
1 0.9 0.8 0.7 Operation Best Fit
0.6 0.5 0.5
0.6
0.7
0.8
0.9
Desuperheater Steam Flow Rate, [ - ]
1
1.0 Operation Best Fit
0.9 0.8 0.7 0.6 0.5 0.5
0.6
0.7
0.8
0.9
1.0
Brine R/C Pump Flow Rate, [ - ]
Figure 3 Energy efficiency of Desuperheater (left) and brine recirculation pump (right) The dimensionless exergy efficiency of brine recirculation (R/C) pump and desuperheater are plotted in Figure 3. The exergy efficiency of desuperheater increases from 0.7 and 0.90 when the steam flow rate is increased from 0.7 to 1. Similarly, the exergy efficiency of brine recirculation pump increases from 0.8 to 1 when the flow is increased from 0.8 to 1, signifying opportunities for improvement in energy efficiency of both the equipments by increasing load on both the equipments. Also, for the fixed
Performance Assessment and Benchmarking of Desalination Plants
1103
flow conditions, the variations in efficiency are huge in case of desuperheater, signifying possible improvements in energy efficiency by reduced variations.
0.13
Operation Best Filt
0.12
0.11
0.10 0.00
0.50
1.00
Sp. Elect. Consumption, [ ]
Sp. Steam Consumption, [ ]
4.2. KPI Calculator Various KPIs, defined in the tool, were configured to plant data and calculated for MSF desalination plant configuration. Trend plots were generated for these KPIs to evaluate their impact on plant performance. The specific steam consumption and specific electricity consumption in desalination plant can be reduced by increasing load factor (Figure 4). This would result in a maximum improvement in plant profit of ~ 0.2 kUSD/h (Figure 5, left). Note that a maximum total profit of 650 kUSD/year is possible based on the current plant production distribution profile. The specific steam consumption in plant can also be reduced by reducing the losses due to excessive dumping of steam to dump condenser (Figure 5, right). The mean values of some of the KPIs, defined in Error! Reference source not found., were also compared against recommended values to identify improvements. As shown, by comparison in Error! Reference source not found., a few KPIs are operating within permissible limits while others can be improved further to improve plant performance.
1.50
3.9
Operation Best Filt
3.7 3.5 3.3 3.1 2.9 2.7 2.5 0.00
Water Production, [ ]
0.50 1.00 Water Production, [ ]
1.50
0.14 Operation Best Fit
0.13 0.12 0.11 0.10 4
5 6 7 8 9 10 % Steam to Dump Condenser, [ ]
0.25 Plant Profit, kUSD/h
Sp. Steam Consumption, [ ]
Figure 4 Specific steam consumption (left) and specific electricity consumption (right) with respect to water production.
0.20
Operation Best Fit
0.15
0.10 0.05
0.00 0.60 -0.05
0.70
0.80
0.90
1.00
1.10
Water Production, [ ]
Figure 5 % Steam consumption vs. Specific steam consumption (left) and Water production vs. Plant profit (right) in an MSF desalination Plant. 4.3. Cost-Benefit estimation In this section, the efficiency estimates of equipments from exergy analysis and improvements in KPIs were translated into cost savings. The estimated cost savings resulting from improved equipments efficiency of brine heater, desuperheater and brine
N. Bhutani et al.
1104
recirculation pump by improving load factor were 17, 21 and 30 kUSD/year, brine blowdown heat recovery was 19 kUSD and reduced steam losses by no dumping of steam to dump condenser was 104 kUSD respectively. Note that savings are tuned to current production of the pilot plant. Further, cost-benefit analysis is feasible with this tool for replacement of fixed drive with variable frequency drive (VFD) for pumps or other capital investments.
Table 1 Calculated KPI for MSF desalination Plant KPI Definition Sp. Steam Consumption in major consumers, tons/m3 water Sp. Electricity Consumption in major consumers, kWh/m3 water % Brine Blowdown, %
Mean Value Recommended 0.12 Least Possible
Distillate To Makeup Ratio, [ ] % Steam To Dump Condenser,
3.22
Least Possible
62.56
Least Possible
0.36
b/w 0.3-0.4
%
8.18
Equal to 0 or Least Possible
o
30.12
Less than equal to 10-15 oC
Degree Superheat of LP steam, C
Degree Superheat of Brine Heater steam, 10.64 o C Delta T Flash MSFSection, oC 57.20 o
Less than equal to 5 oC Highest Possible
Delta T, SeaWater (Inlet – Reject), C
7.87
Less than equal to 10 oC
Delta T BrineHeater (for Brine), oC
6.90
Less than equal to 5 oC
5. Conclusions The energy assessment and benchmarking tool was used to identify opportunities for energy efficiency improvements and translate them into potential cost savings for the pilot customer. With a user-friendly graphic user interface (GUI), a wide range of industrial desalination plants/configurations (thermal, hybrid, membrane based) can be analyzed very quickly. References [1]. Z. Elimelech M and Philip WA., The Future of sea water desalination: Energy, Technology, and the environment, Science, vol. 333, no. 6043, pp. 712-717, August 2011. [2]. Sharqawy M H., et. al., On exergy calculation of sea water with applications in desalination systems, International Journal of Thermal Science, vol. 50, pp. 187-196, 2011. [3]. Kahraman N., and Cengel Y. A., Exergy analysis of a MSF distillation plant, Energy conservation and management, vol. 46, pp. 2625-2636, 2005. [4]. Cerci Y., Exergy analysis of a reverse osmosis plant in California, Desalination, vol., 142, pp. 257-266, 2002. [5]. Macedonio F. and Drioli E., An exergy analysis of membrane desalination system. Desalination, vol. 261, pp. 293-299, 2010. [6]. Ataei A. and Yoo C., Combined pinch and exergy analysis for energy efficiency optimization in a steam power plant, International Journal of the Physical science, vol. 5(7), pp. 1110-1123, 2010. [7]. Rosen M. A. and Bulucea C. A., Using exergy to understand and improve the efficiency of Electrical power technologies, Entropy, vol. 11, pp. 820-835, 2009.