Process Energy Systems: Control, Economic, and Sustainabili - PowerPoint Presentation

Slide1

Process Energy Systems: Control, Economic, and Sustainability Objectives

Jeffrey J. SiirolaThomas F. EdgarFOCAPO/CPC 2012Savannah, GA

1Slide2

Outline

Elements of sustainabilityNew emphasis on greenhouse gas emissionsCarbon management by energy reductionSmart manufacturing, process control, and operations optimizationDynamic energy minimizationNext generation power systems (smart grids)

Thermal energy storage and process control

2Slide3

Elements of Sustainability

Health and safetyEnvironmental protectionMaterials and energy efficiencyProduct stewardship

Corporate

citizenship

Triple bottom line

3Slide4

Sustainability Issues Addressed During Design

Inherent safety principlesHigh yield reaction chemistriesMaterial recovery and recycleHeat integrationMulti-effect separationCarbon management remains particularly difficult and expensive

4Slide5

Proposed Legislatively Mandated US GHG Reductions

http://www.wri.org/climate/topic_content.cfm?cid=4265

5Slide6

CO

2 Policy AlternativesRegulated CO2Recent EPA announcement on reporting requirementsCap 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

6Slide7

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

7Slide8

Base Case Carbon Capture and Sequestration Technology

Post combustion monoethanolamine absorption30% parasitic energy requirement for coal-fired powerplant>70% increase in electric power costChilled ammonia alternativeDOE Carbon Capture Simulation Initiative to address and reduce commercialization risks

8Slide9

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)

9Slide10

Reducing Carbon Footprint in Process Plants

Fuel swapping (natural gas for coal)Conversion to non-fossil energy sources (nuclear, solar, or biomass)Reduce energy requirementsUse less energy-intensive chemistry/unit operationsIncrease heat and power integrationRetrofits difficult to justify economically unless accompanied by capacity expansion

Operate processes with additional objective to minimize energy consumption

10Slide11

Perspective of this Presentation

Most carbon dioxide emission comes from fossil fuel combustionMaximize energy efficiency ≡ minimize carbon footprintFocus on process operation and control (not design)Assume use of existing infrastructure to maximize thermal efficiencyProgress requires a systems approach11Slide12

Optimization

of OperationsReduce energy consumptionImprove yieldsReduce pollutantsIncrease processing ratesIncrease profitability

12Slide13

Some Observations

Most plants do not monitor energy consumption on an individual unit operations basis, but only total plant usage for accounting purposesProcesses may be designed for energy efficiency, but do not include degrees of freedom and manipulated variables to minimize energy utilization during operationsSchemes 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 disturbances13Slide14
Slide15

21st Century Business Drivers for Process Control

(Edgar, 2004)Deliver a product that meets customer specifications consistentlyMaximize the cost benefits of implementing and supporting control and information systemsMinimize product variabilityMeet safety and regulatory (environmental) requirementsMaximize asset utilization and operate the plant flexiblyImprove the operating range and reliability of control and information systems and increase the operator’s span of control

15Slide16

16Slide17

17

Transformation of Variation from the Temperature to Flow for a Reactor Feed Preheater (Downs et al., 1991)Slide18

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” MPCEnergy 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 optimizedSwapping 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 PSE18Slide19

Addition of Sensors and Manipulated Variables to Minimize Dynamic Energy Use

In a distillation column, maximize efficiency by operating near the flooding pointBalance yield improvement vs. energy useAdd MV’s with multiple feed points, bypassesAdd hard and soft sensors for improved real-time modeling (e.g., Dzyacky flooding predictor based on pressures, temperatures, levels, flow rates)Slide20

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 towerOpen 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 unitsIf 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?Slide21

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 reliabilityPower 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/demandPermits increased use of intermittent renewable power sources such as solar or wind energy and increases need for energy storage21Slide22

Electricity Demand Varies

throughout the Day

Source: ERCOT Reliability/Resource Update 2006

22Slide23

Today’s Grid

Smart Grid 1.0

23Slide24

Smart Grid 2.0

Tomorrow’s Grid

24Slide25

Three Types of Utility Pricing

Time-of-use (TOU) – fixed pricing for set periods of time, such as peak period, off peak, and shoulderCritical 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 daysReal time pricing (RTP) – retail energy price tied to the wholesale rate, varying throughout the day25Slide26

26Slide27

Future Industrial Environment

Stronger focus on energy use(corporate energy czars?)Increased energy efficiency and decreased carbon footprintEnergy use measured and optimized for each unit operationIncreased use of renewable energy(e.g., solar thermal and biomass) and energy storageInterface with smart grids

27Slide28

28Slide29

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 timeUsing 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)

29Slide30

TES Economics are Attractive

High utility demand costsUtility 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 variationsShort duration loadsInfrequent or cyclical loads

30Slide31

Energy flows in a combined heat and power system with thermal storage

(Wang, et al. 2010)Slide32

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)Slide33

Conclusions

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