1. Process Energy Systems: Control, Economic, and Sustainability Objectives Jeffrey J. Siirola Thomas F. Edgar FOCAPO/CPC 2012 Savannah, GA 1

2. Outline Elements of sustainability New emphasis on greenhouse gas emissions Carbon management by energy reduction Smart manufacturing, process control, and operations optimization Dynamic energy minimization Next generation power systems (smart grids) Thermal energy storage and process control 2

3. Elements of Sustainability Health and safety Environmental protection Materials and energy efficiency Product stewardship Corporate citizenship Triple bottom line 3

4. Sustainability Issues Addressed During Design Inherent safety principles High yield reaction chemistries Material recovery and recycle Heat integration Multi-effect separation Carbon management remains particularly difficult and expensive 4

5. Proposed Legislatively Mandated US GHG Reductions http://www.wri.org/climate/topic_content.cfm?cid=4265 5

6. CO 2 Policy Alternatives Regulated CO 2 – Recent EPA announcement on reporting requirements Cap and Trade – Establishes firm but decreasing limits on CO 2 emissions – Auctioning/trading of emissions permits Carbon Tax – Price predictability – Favored by large chemical companies – Apply to all carbon sources 6

7. CO 2 Absorption/Stripping of Power Plant Flue Gas Flue Gas With 90% CO 2 Removal Stripper Flue Gas In Rich Solvent CO2 for Transport & Storage LP Steam Absorber Lean Solvent Use 30% of power plant output 7

8. Base Case Carbon Capture and Sequestration Technology Post combustion monoethanolamine absorption – 30% parasitic energy requirement for coal-fired powerplant – >70% increase in electric power cost Chilled ammonia alternative DOE Carbon Capture Simulation Initiative to address and reduce commercialization risks 8

9. U.S. Industrial/Building Sector Industrial energy usage = 35 quads (total = 100 quads) This sector accounts for about one-third of total U.S. GHG emissions By 2030, 16% growth in U.S. energy consumption, which will require additional 200 GW of electrical capacity (EIA) Energy efficiency goals of 25% reduction in energy use by 2030 (McKinsey and National Academies Press reports) 9

10. Reducing Carbon Footprint in Process Plants Fuel swapping (natural gas for coal) Conversion to non-fossil energy sources (nuclear, solar, or biomass) Reduce energy requirements – Use less energy-intensive chemistry/unit operations – Increase heat and power integration – Retrofits difficult to justify economically unless accompanied by capacity expansion – Operate processes with additional objective to minimize energy consumption 10

11. Perspective of this Presentation Most carbon dioxide emission comes from fossil fuel combustion Maximize energy efficiency ≡ minimize carbon footprint Focus on process operation and control (not design) Assume use of existing infrastructure to maximize thermal efficiency Progress requires a systems approach 11

12. Optimization of Operations Reduce energy consumption Improve yields Reduce pollutants Increase processing rates Increase profitability 12

13. Some Observations Most plants do not monitor energy consumption on an individual unit operations basis, but only total plant usage for accounting purposes Processes may be designed for energy efficiency, but do not include degrees of freedom and manipulated variables to minimize energy utilization during operations Schemes control for desired throughput and product fitness-for-use attributes (composition, purity, color, etc.), but use utilities (energy) to achieve these goals and to reject disturbances 13

15. 21st Century Business Drivers for Process Control (Edgar, 2004) Deliver a product that meets customer specifications consistently Maximize the cost benefits of implementing and supporting control and information systems Minimize product variability Meet safety and regulatory (environmental) requirements Maximize asset utilization and operate the plant flexibly Improve the operating range and reliability of control and information systems and increase the operator’s span of control 15

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17. 17 Transformation of Variation from the Temperature to Flow for a Reactor Feed Preheater (Downs et al., 1991)

18. More Observations Most multivariable algorithms (like MPC or LQG) do not assign an economic value to the manipulated variable moves, although some research efforts have been oriented towards “economic” MPC Energy reuse adding heat and power integration will create unit and control loop interactions and new disturbance patterns, making control strategies more complex. Integer (on-off) variables for equipment such as chillers will need to be optimized Swapping thermal and electrical forms of energy can have unexpected utilities systems impacts (dynamics and control) Attempting to control carbon emissions as well as energy usage will require new research investigations in PSE 18

19. Addition of Sensors and Manipulated Variables to Minimize Dynamic Energy Use In a distillation column, maximize efficiency by operating near the flooding point Balance yield improvement vs. energy use Add MV’s with multiple feed points, bypasses Add hard and soft sensors for improved real-time modeling (e.g., Dzyacky flooding predictor based on pressures, temperatures, levels, flow rates)

20. Predictive Modeling Needed to Manage Dynamic Energy Use – Refinery Example Increased throughput to a crude distillation unit must consider operating variables for crude tankage, pumps, preheat trains, and distribution of cuts from the tower Open up valves and let all equipment ramp up? Is there an optimum way that incorporates energy use? Perhaps a given ramp rate will result in more energy efficient performance of downstream units If an abundance of fuel gas will be available in one hour, will that facilitate a much more energy efficient ramp up, rather than sending the excess to flare?

21. What is a Smart Grid? Delivery of electric power using two-way digital technology and automation with a goal to save energy, reduce cost, and increase reliability Power will be generated and distributed optimally for a wide range of conditions either centrally or at the customer site, with variable energy pricing based on time of day and power supply/demand Permits increased use of intermittent renewable power sources such as solar or wind energy and increases need for energy storage 21

22. Electricity Demand Varies throughout the Day Source: ERCOT Reliability/Resource Update 2006 22

23. Today’s Grid Smart Grid 1.0 23

24. Smart Grid 2.0 Tomorrow’s Grid 24

25. Three Types of Utility Pricing Time-of-use (TOU) – fixed pricing for set periods of time, such as peak period, off peak, and shoulder Critical peak pricing (CPP) – TOU amended to include especially high rates during peak hours on a small number of critical days; alternatively, peak time rebates (PTR) give customers rebates for reducing peak usage on critical days Real time pricing (RTP) – retail energy price tied to the wholesale rate, varying throughout the day 25

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27. Future Industrial Environment Stronger focus on energy use(corporate energy czars?) Increased energy efficiency and decreased carbon footprint Energy use measured and optimized for each unit operation Increased use of renewable energy(e.g., solar thermal and biomass) and energy storage Interface with smart grids 27

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29. Thermal Energy Storage Thermal energy storage (TES) systems heat or cool a storage medium and then use that hot or cold medium for heat transfer at a later point in time Using thermal storage can reduce the size and initial cost of heating/cooling systems, lower energy costs, and reduce maintenance costs; if electricity costs more during the day than at night, thermal storage systems can reduce utility bills further Two forms of TES systems are currently used – A material that changes phase, most commonly steam, water or ice (latent heat) – A material that just changes the temperature, most commonly water (sensible heat) 29

30. TES Economics are Attractive High utility demand costs Utility time-of-use rates (some utilities charge more for energy use during peak periods of day and less during off-peak periods) High daily load variations Short duration loads Infrequent or cyclical loads 30

31. Energy flows in a combined heat and power system with thermal storage (Wang, et al. 2010)

32. Thermal Energy Storage Operating Strategy with Four Chillers 32 -Chillers 1& 4 are most efficient, 3 is least efficient -Chiller 1 is variable frequency (a) Experience-based (operator-initiated) -No load forecasting -Uses least efficient chiller (Chiller 3) (b) Load forecasting + optimization -Uses most efficient chillers (avoids Chiller 3) (c) Load forecasting + TES + optimization -Uses only two most efficient chillers (a)(b) (c)

33. Conclusions Many opportunities to improve energy efficiency in the process industries Energy efficiency ≡ sustainability (carbon footprint) Smart grids and energy storage will change the power environment for manufacturing Development of new real-time modeling, control, and optimization tools will be critical to deal with this dynamic environment A focus on energy comparable to the current emphasis on safety would yield significant improvements in energy efficiency