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Analysing cognitive work of hydroelectricity generation in a dynamic deregulated market. Penelope M. Sanderson Cognitive Engineering Research Group The University of Queensland Brisbane, Australia CWA workshop University of Washington Wednesday 3 November 2004. Acknowledgments.

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analysing cognitive work of hydroelectricity generation in a dynamic deregulated market

Analysing cognitive work of hydroelectricity generation in a dynamic deregulated market

Penelope M. Sanderson

Cognitive Engineering Research Group

The University of Queensland

Brisbane, Australia

CWA workshop

University of Washington

Wednesday 3 November 2004

acknowledgments
Acknowledgments
  • Collaborators
    • Professor William Wong (Middlesex University)
    • Dr Rizah Memisevic (CERG, Univ of Queensland)
    • Mr Sanjib Choudhury (Snowy Hydro Limited)
  • Funding
    • Australian Research Council SPIRT grant (industry partner Snowy Hydro Limited)
challenges to cwa approach
Challenges to CWA approach
  • Goal: Suggestions for advanced interfaces to supplement a major installed base
  • Challenges at all points on design life cycle
    • Modeling
      • Need to represent complex interactions and constraints between (highly distributed) physical and (secret) economic systems
    • Design
      • Finding metaphors that work on top of existing displays
    • Evaluation
      • Assessing against EID hallmarks of better performance.
slide4

Elements of hydro

Dam

Reservoir/Storage

Spill

Dam

Penstocks

  • Power Station
    • 4 generators
    • 2 generator/pumps

Inflow

  • Switching Yard
    • Circuit breakers
    • Transformers

Transmission lines

modeling hydropower generation as a physical work domain

Diversion

Diversion

Diversion

Diversion

ModelingHydropower generation as a physical work domain

Irrigation goals

Security goals

Generation goals

Irrigation goals

Generation goals

FP

FP

FP

FP

Generation goals

Generation goals

Irrigation goals

Irrigation goals

Mass store

Mass in

Mass store

Mass store

Mass store

Mass in

Mass in

Mass in

AF

AF

AF

AF

Mass out

Mass transfer

Mass out

Mass out

Mass out

Mass transfer

Mass transfer

Mass transfer

Electrical energy

Energy demand

Kinetic energy

Potential energy

Electrical energy

Electrical energy

Electrical energy

Kinetic energy

Kinetic energy

Kinetic energy

Potential energy

Potential energy

Potential energy

Transmission

Generation

GF

GF

GF

GF

Storage

Inflow

Storage

Storage

Storage

Storage

Storage

Storage

Irrigation

Spill

Irrigation

Irrigation

Irrigation

Release water

Transmit electricity

Make electricity

Direct water

Hold water

PFu

PFu

PFu

PFu

Release water

Release water

Release water

Make electricity

Make electricity

Make electricity

Direct water

Direct water

Direct water

Hold water

Hold water

Hold water

Transformers

Gates

Turbines

Dams

Pipes

Lines, buses

Lakes

Valves

Generators

Tunnels

PFo

PFo

PFo

PFo

Turbines

Gates

Gates

Gates

Turbines

Turbines

Turbines

Dams

Dams

Dams

Pipes

Pipes

Pipes

Lakes

Lakes

Lakes

Valves

Valves

Valves

Generators

Generators

Generators

Tunnels

Tunnels

Tunnels

Circuit breakers

Pumps

(Gravity)

Tunnels

Tunnels

Tunnels

Pipes

Pipes

Pipes

Pipes

Pipes

Pipes

snowy control centre 1998
Snowy control centre: 1998
  • Pre-deregulation of electricity market
snowy control centre 2000
Snowy control centre: 2000
  • Immediately post deregulation, coping with market using hybrid control system
slide8

Snowy control centre: 2003

  • Building in flexible views
  • Removal of pre-deregulation legacy systems
snowy control centre busy summer day
Snowy control centre: Busy summer day
  • Dynamism—actual dispatched targets (generation targets) exceed even most recently updated estimates
modeling traditional functions modeled and displayed
ModelingTraditional functions modeled and displayed

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Constraints on generation

Constraints on generation

Constraints on generation

Constraints on generation

Capacity,

Capacity,

Capacity,

Capacity,

hydrology predictions

availability

availability

availability

availability

Mass transfer

Transmission

Energy transfer

Mass transfer

Mass transfer

Mass transfer

Energy transfer

Energy transfer

Energy transfer

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

earnings

earnings

earnings

earnings

releases

releases

releases

releases

Irrigation earnings

Electricity earnings

Irrigation market

Irrigation market

Irrigation market

Electricity market

Energy market

Energy market

Constraints on sales and prices

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Meteorology and

Weather, contingencies,

agricultural needs

agricultural needs

seasonal predictions,

competitors

competitors

behaviour

behaviour

modeling need to see relationships between areas
ModelingNeed to see relationships between areas

Uncertainties, constraints, are crucial

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Constraints on generation

Constraints on generation

Constraints on generation

Constraints on generation

Capacity,

Capacity,

Capacity,

Capacity,

hydrology predictions

availability

availability

availability

availability

Mass transfer

Transmission

Energy transfer

Mass transfer

Mass transfer

Mass transfer

Energy transfer

Energy transfer

Energy transfer

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

earnings

earnings

earnings

earnings

releases

releases

releases

releases

Irrigation earnings

Electricity earnings

Irrigation market

Irrigation market

Irrigation market

Electricity market

Energy market

Energy market

Constraints on sales and prices

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Meteorology and

Weather, contingencies,

agricultural needs

agricultural needs

seasonal predictions,

competitors

competitors

behaviour

behaviour

design some current high level displays for monitoring
DesignSome current high-level displays for monitoring

Transmission network

Short-term electricity market targets

Hydraulic network

Transmission constraints

modeling connection of generation and transmission constraints

Diversion

Diversion

Diversion

Diversion

ModelingConnection of generation and transmission constraints

Irrigation goals

Security goals

Generation goals

Irrigation goals

Generation goals

FP

FP

FP

FP

Generation goals

Generation goals

Irrigation goals

Irrigation goals

Mass store

Mass in

Mass store

Mass store

Mass store

Mass in

Mass in

Mass in

AF

AF

AF

AF

Mass out

Mass transfer

Mass out

Mass out

Mass out

Mass transfer

Mass transfer

Mass transfer

Electrical energy

Energy demand

Kinetic energy

Potential energy

Electrical energy

Electrical energy

Electrical energy

Kinetic energy

Kinetic energy

Kinetic energy

Potential energy

Potential energy

Potential energy

Transmission

Generation

GF

GF

GF

GF

Storage

Inflow

Storage

Storage

Storage

Storage

Storage

Storage

Irrigation

Spill

Irrigation

Irrigation

Irrigation

Release water

Transmit electricity

Make electricity

Direct water

Hold water

PFu

PFu

PFu

PFu

Release water

Release water

Release water

Make electricity

Make electricity

Make electricity

Direct water

Direct water

Direct water

Hold water

Hold water

Hold water

Gates

Dams

Pipes

Lines, buses

Lakes

Valves

Generators

Tunnels

Turbines

Transformers

PFo

PFo

PFo

PFo

Gates

Gates

Gates

Dams

Dams

Dams

Pipes

Pipes

Pipes

Lakes

Lakes

Lakes

Valves

Valves

Valves

Generators

Generators

Generators

Tunnels

Tunnels

Tunnels

Circuit breakers

Pumps

(Gravity)

Tunnels

Tunnels

Tunnels

Pipes

Pipes

Pipes

design integrate with first principles view of power generation
DesignIntegrate with first principles view of power generation

Limiting circle

(Power circle)

Synchronous condensor mode (reactive power)

Q

+MVAr

Pumping mode

S

Generating mode

Reactive power positive

Capacity of generating units currently running

P

Active power consumed

Active power generated

+MW

-MW

Reactive power negative

Operational limit on (complex) power transmission

Physical limit on (complex) power transmission

-MVAr

S = SQRT [ P2 + Q2 ]

Complex power = SQRT [ Active power2 + Reactive power2 ]

design first principles view market targets and water
DesignFirst principles view : Market targets and water

MARKET REAL-TIME

Add market targets

Add contingency services

Add present operating point

TRANSMISSION

Add complex power upper constraint from transmission line loading

WATER MASS

Add pond levels and how they are being controlled

design first principles view severe transmission constraint
DesignFirst principles view: Severe transmission constraint

TRANSMISSION

Transmission capacity is less than generation capacity

modeling need to see earnings and risks

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Constraints on generation

Constraints on generation

Constraints on generation

Constraints on generation

Capacity,

Capacity,

Capacity,

Capacity,

hydrology predictions

availability

availability

availability

availability

Mass transfer

Transmission

Energy transfer

Mass transfer

Mass transfer

Mass transfer

Energy transfer

Energy transfer

Energy transfer

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

Constraints on

earnings

earnings

earnings

earnings

releases

releases

releases

releases

Irrigation earnings

Electricity earnings

Irrigation market

Irrigation market

Irrigation market

Electricity market

Energy market

Energy market

Constraints on sales and prices

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Uncertainty

Uncertainty

Uncertainty

Uncertainty

:

:

:

:

Meteorology and

Meteorology and

Weather, contingencies,

agricultural needs

agricultural needs

seasonal predictions,

competitors

competitors

behaviour

behaviour

ModelingNeed to see earnings and risks
modeling representing financial risk21
ModelingRepresenting financial risk
  • Market as intentional—rule-based but tightly coupled to transmission network (cf. Achonu & Jamieson, 2003)
  • Some CWA work to date on modeling financial work domains:
    • WDA of management of structured product category of mutual fund (Achonu & Jamieson, 2003)
    • EID display for fundamental analysis of investment prospects (Dainoff, Dainoff, & McFeeters, 2004)
    • EID display for exposing gambling risks/odds to potential problem gamblers (Burns & Proulx, 2002)
    • Flow of value through a company (Smith, in Rasmussen, Pejtersen, & Goodstein, 1994)
modeling representing financial risk22
Modeling Representing financial risk
  • Market behavior not predictable from laws of nature
  • Based on intentions of traders, demand for electricity, forecasts, risk appetites and competitive responses of other traders(Sanderson, Memisevic, & Wong, 2004)
    • Trading strategies are secret
    • Functional structure (why/how) distributed and obscure
    • Operation of market continually changes as situation changes and strategies evolve—evolving economic system
  • High-level application of EID principles points to integration needs.
modeling market priorities and functions
ModelingMarket:priorities and functions

Irrigation goals

Generation goals

Profit

Irrigation goals

FP

FP

FP

FP

Irrigation goals

Irrigation goals

Maximise earnings: costs ratio

Balance earnings: risk ratio

Minimise opportunity costs

AF

AF

AF

AF

Risk choices

Earnings targets

Configuration of resources

Production targets

Earnings

Gains

Spot market

Hedge contract gains

FCAS market

Settlements residue

System restart

Reactive power control

Losses

Spot market

Hedge contract losses

Causer pays

Fines

Settlements residue

System restart

GF

GF

GF

GF

Settlements

Risk profile

Trading strategy

Daily operations plan

Market (re)bid

Generation

schedules

PFu

PFu

PFu

PFu

PFo

PFo

PFo

PFo

design risk exposure hidden

Present

Future

Past

Present

Future

DesignRisk exposure hidden

Electricity to be made and market price for MW/hour

Plant set-up throughout day and amount of electricity made

design risk exposure revealed
DesignRisk exposure revealed
  • Future risk—profile of financial instruments generating or losing income over time

Present

Past

Future

evaluation microworld development
EvaluationMicroworld development
  • Completion of SnowySim(Memisevic, Sanderson, Choudhury & Wong, 2004; Memisevic, Choudhury, Sanderson & Wong, 2004)
    • Reproduces major functions and displays
    • Two laptop computers driving eight 19” displays
    • Validated with Scheme controllers in 2003
  • Preparation of abnormal scenarios
    • Test unexpected events as well as normal operations
  • Participant pool: population pool of 7 controllers, 12 coordinators—extremely restricted.
evaluation translation of useful measures
EvaluationTranslation of useful measures
  • Conventional figures of merit
    • Time to detect, time to diagnose, situational awareness (S1, S2, S3), “mental model” of operation, trust in displays
  • Advanced figures of merit (Crone, Sanderson & Naikar, 2003)
    • Control adaptation (high within-subject S2 in use of low-level processes, low within-subject S2 in capture of high-level goals) (Yu, Lau, Vicente, & Carter, 2002; for similar between-subject pattern see Reising & Sanderson, 2000)
    • Control adaptation difficult to operationalise for market-driven scheme control
      • Any adaptation or compensation is subject to central market clearing mechanism and five-minute delay before action possible.
evaluation empirical framework
EvaluationEmpirical framework
  • Looking for signs of better performance with displays based on these ideas (Xilin Li, PhD in progress at UQ)
    • Test sensitivity of figures of merit for performance
    • Test usefulness of displays
  • Experimental conditions
    • Current interface (baseline)
    • Current interface minus native higher-level displays (sensitivity)
    • Advanced interface with current plus EID (usefulness)
conclusions
Conclusions
  • Many aspects of market subdomain difficult to model
  • Moving from summary analysis to design:
    • High-level integration of sources of constraints and uncertainties provides framework
    • Search for first-principles views into the system
    • Add constraints and boundaries that should guide behaviour.
  • Bounded design search space—first driven by analysis, then recognition-primed discovery of solutions