Energy Optimization at a Chemical Industry Enterprise
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ISRN LUTMDN/TMHP—13/5269—SE ISSN 0282-1990 Energy optimization at a chemical industry enterprise Case study – Perstorp AB Sandra Leksell and Anna Pärsdotter Thesis for the Degree of Master of Science Department of Energy Sciences Faculty of Engineering LTH LUND UNIVERSITy P O Box 118, S-221 00 Lund, Sweden This master’s thesis, Energy optimization at a chemical industry enterprise, has been performed at Perstorp Specialty Chemicals AB. The thesis has been carried out in cooperation between Lund University, Faculty of Engineering, Department of Energy Sciences, and Perstorp AB. Energy optimization at a chemical industry enterprise Case study – Perstorp AB Sandra Leksell and Anna Pärsdotter March 2013 Thesis for the Degree of Master of Science ISRN LUTMDN/TMHP—13/5269—SE © 2013 Sandra Leksell, Anna Pärsdotter and Energy Sciences Efficient Energy Systems Department of Energy Sciences Lund University - LTH Box 118, 221 00 Lund, Sweden www.ees.energy.lth.se Acknowledgment This master's thesis has been performed at Perstorp Specialty Chemicals AB in Perstorp, located in Scania, Sweden. The project has been carried out in cooperation between Lund University, Faculty of Engineering, Department of Energy Sciences and Perstorp AB. The aim of the thesis was to evaluate the energy consumption at the chemical industry Perstorp AB, this was performed by developing statistical models and evaluating the energy management at the enterprise. We would like to thank our supervisor Patrick Lauenburg and the examiner Jurek Pyrko at Lund University, Faculty of Engineering, Department of Energy Sciences, and our supervisor Daniel Hansson at Perstorp for all their help and time spent on this project. At Lund University, Faculty of Engineering, De- partment of Mathematics we thank Lena Zetterqvist who has helped us with mathematical statistics questions. Finally, we would like to thank all employees at Perstorp who have helped us during our time in Perstorp, without them we would never have completed this master's thesis. A special thank goes to the Process Engineers Tony Persson, Petter Lind, Sixten Dahlblom and Josefine Cragnell for their guidance. Lund, March 2013 Anna P¨arsdotter and Sandra Leksell 1 Executive summary Title: Energy optimization at a chemical industry enterprise Case study - Perstorp AB Authors: Sandra Leksell and Anna P¨arsdotter Supervisors: Patrick Lauenburg, PhD, Dept. of Energy Sciences, Faculty of En- gineering, Lund University and Daniel Hansson, Technical Manager, Perstorp Specialty Chemicals AB Background: The industrial sector in Sweden consumed 152.4 TWh energy in 2010, which represented 36% of Sweden's total energy that year. The chem- ical industry accounted for 11.4 TWh (7.5%). Energy efficiency mea- sures and improvements are given priority by enterprises today, due to increasing energy prices and implemented energy policies. To reduce the competitive threat caused by increasing energy prices, Swedish companies have two options; either negotiate a lower energy price from the energy companies or work internally with energy efficiency measures. Industries located in colder climates, having a temperature dependent production, are additionally affected by increased energy prices. Perstorp Specialty Chemicals initiated this master's thesis, because they have experienced a variation in steam consumption at their factories. They believed the reasons behind the variety were that production rate affected the energy consumption, that a cold outdoor temperature resulted in energy leakage and that the base load was similar throughout time. Despite this, they have never per- formed any thorough energy analysis that confirms to what extent these factors affect the energy usage in the factories. Objective: The objective of this master's thesis was to evaluate the energy con- sumption, mainly steam usage, at the chemical industry Perstorp AB and this was performed by developing statistical models and evalu- ating the energy management at the enterprise. Methodology: This master's thesis is divided in two parts, and several different methods have been employed in both. The first part is an Energy usage analysis, which began by creating an overview of the produc- tion site and factories. The overview was made after visits to the factories and studies of theirs flow charts. Finally the processes were discussed with employees at Perstorp. Relevant and available energy data were then assembled and evaluated. An energy audit, founded on the energy data, for four polyol factories was performed, where large energy consumers were identified. Later, the energy perfor- mance of these factories was evaluated. The latter included a study of which variables that affected the steam consumption, and it was based on the statistical model multiple linear regression. 2 The second part, Evaluating Perstorp's energy management, began with a literature study and an interview with a PhD-candidate at Lund Faculty of Engineering. After this, interviews were performed with employees at Perstorp to gain knowledge on how the energy management was handled at the company. After the interviews, an overview was made of the energy management and working method- ology. Energy efficiency measures within the company and possible improvements regarding their management were suggested. Conclusion: The main conclusion from the Energy usage analysis, was that the statistical method used, multiple linear regression, can only be ap- plied for some systems. The method is straightforward, proving a correlation, in this case between steam usage and other variables. If the system was complex, with reflows, heat recovery, leakage or other factors affecting the steam consumption, the modelling gave a poor result. However, if the system is simpler, e.g. with a product inflow heat exchanged against the steam flow, or heating of compo- nent, where the steam consumption correlates to the temperature, the method can be of great use. The models for two out of four factories resulted in a better correlation. One of the factories with poorer result was examined more carefully with diverting result for the components. Some of the steam consumption should be corre- lated towards the outdoor temperature instead of production rate, when calculating the company's energy budget. Regarding the second part; the energy management at Perstorp is organized, although it can be improved. The impression the authors got after finishing the interviews at Perstorp was that energy is an im- portant issue, though it is not prioritized from the company's board. Furthermore, the Energy Coordinator believes that the level of am- bition can increase at the company. Nevertheless, Perstorp has some good examples of well-practiced energy management: weekly discus- sion regarding energy ratios, a follow up if the ratio is higher than expected and an Energy Coordinator that wants to improve their ambitions. Still, there are some fields within the energy manage- ment at Perstorp that can be improved, most importantly creating an Energy group, which can get a comprehensive view concerning en- ergy issues. Additionally, Perstorp can improve the follow-ups after energy projects are implemented, create long-term energy goals and make the staff aware of these and have better training for the staff. Keywords: Energy efficiency, Process industry, Steam consumption, Multiple lin- ear regression, Energy management system, Perstorp AB 3 Contents 1 Introduction 7 1.1 Background . 7 1.2 Objective ............................... 8 1.3 Constrains . 8 1.4 Method ................................ 8 2 Perstorp AB 10 2.1 Description of Perstorp Specialty Chemicals AB . 10 2.1.1 Energy usage and production . 10 3 Theory I - Energy usage analysis 12 3.1 Process industry . 12 3.1.1 Steam as an energy carrier . 12 3.1.2 Industrial components . 12 3.2 Statistical methods . 14 3.2.1 Multiple linear regression . 14 3.2.2 Influence of variables . 15 3.2.3 Determination coefficient - R2value . 15 3.2.4 Expected values . 16 3.2.5 Multicollinearity . 16 4 Theory II - Energy management 18 4.1 Management control measures in Sweden . 18 4.1.1 Program for energy efficiency . 18 4.1.2 Energy management system . 18 4.1.3 Tradable renewable electricity certificates . 19 4.1.4 European Union Emission Trading Scheme . 20 4.2 Energy management in industrial companies . 20 4.2.1 Driving forces for energy efficiency . 21 4.2.2 Barriers to energy efficiency . 22 4.2.3 Establishing change within an organization . 24 5 Result and discussion I - Energy usage analysis 27 5.1 Introduction to the polyol factories . 27 5.2 Problems regarding measurements . 29 5.2.1 Valid data from the factories . 30 5.3 Examined variables . 31 5.3.1 Production rate . 31 5.3.2 Outdoor temperature . 31 5.3.3 Cooling water temperature . 31 5.3.4 Water concentration in a factory . 32 5.3.5 Product flow in a factory . 32 5.4 Polyol A . 32 5.4.1 Chosen data . 32 5.4.2 Statistical result for main meter . 33 5.4.3 Expected steam consumption . 33 5.4.4 Components for Polyol A . 35 5.4.5 Adding new regressor variables to the total model . 51 4 5.4.6 Total model with fewer days . 52 5.4.7 Discussion - Polyol A . 53 5.5 Polyol B . 57 5.5.1 Chosen data . 58 5.5.2 Statistical result for main meter . 58 5.5.3 Expected steam consumption . 59 5.5.4 Adding new regressor variables to the total model . 61 5.5.5 Discussion - Polyol B . 62 5.6 Polyol C . 64 5.6.1 Chosen data . 64 5.6.2 Statistical result for main meter . 65 5.6.3 Expected steam consumption . 65 5.6.4 Discussion - Polyol C . 67 5.7 Polyol D . 67 5.7.1 Chosen data . 68 5.7.2 Statistical result for main meter . 68 5.7.3 Expected steam consumption . 68 5.7.4 Discussion - Polyol D . 70 5.8 Summary of the polyols . 70 5.9 Discussion - Energy usage analysis .