Process Energy Systems: Control, Economic, and

Sustainability Objectives

Jeffrey J. SiirolaThomas F. Edgar

FOCAPO/CPC 2012Savannah, GA

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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

Elements of Sustainability

• Health and safety• Environmental protection• Materials and energy efficiency• Product stewardship• Corporate citizenship• Triple bottom line

3

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

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Proposed Legislatively Mandated US GHG Reductions

http://www.wri.org/climate/topic_content.cfm?cid=42655

CO2 Policy Alternatives

• Regulated CO2

– Recent EPA announcement on reporting requirements

• Cap and Trade– Establishes firm but decreasing limits on CO2 emissions

– Auctioning/trading of emissions permits

• Carbon Tax– Price predictability– Favored by large chemical companies– Apply to all carbon sources

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CO2 Absorption/Stripping of Power Plant Flue Gas

Flue Gas With 90% CO2

RemovalS

tripp

er

Flue Gas In

Rich Solvent

CO2 forTransport& Storage

LP Steam

Ab

sorber

Lean Solvent

Use 30% of power plant output

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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

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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)

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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

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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 approach11

Optimization of Operations

• Reduce energy consumption• Improve yields• Reduce pollutants• Increase processing rates• Increase profitability

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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

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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

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Transformation of Variation from the Temperature to Flow for a Reactor Feed

Preheater (Downs et al., 1991)

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

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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)

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?

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

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Electricity Demand Varies throughout the Day

Source: ERCOT Reliability/Resource Update 2006 22

Today’s Grid

Smart Grid 1.0

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Smart Grid 2.0

Tomorrow’s Grid

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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

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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 grids27

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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)

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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

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

Thermal Energy Storage Operating Strategy with Four Chillers

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-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)

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