Analysing cognitive work of hydroelectricity generation in a dynamic deregulated market

1. 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

2. 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)

3. 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.

4. Elements of hydro Dam Reservoir/Storage Spill Dam Penstocks • Power Station • 4 generators • 2 generator/pumps Inflow • Switching Yard • Circuit breakers • Transformers Transmission lines

5. 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

6. Snowy control centre: 1998 • Pre-deregulation of electricity market

7. Snowy control centre: 2000 • Immediately post deregulation, coping with market using hybrid control system

8. Snowy control centre: 2003 • Building in flexible views • Removal of pre-deregulation legacy systems

9. Snowy control centre: Busy summer day • Dynamism—actual dispatched targets (generation targets) exceed even most recently updated estimates

10. 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

11. DesignEnd-user authoring of displays to fill gaps

12. 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

13. DesignSome current high-level displays for monitoring Transmission network Short-term electricity market targets Hydraulic network Transmission constraints

14. 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

15. 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 ]

16. 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

17. DesignFirst principles view: Severe transmission constraint TRANSMISSION Transmission capacity is less than generation capacity

18. DesignFirst principles view: Source of transmission constraint

19. 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

20. ModelingRepresenting financial risk

21. 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)

22. 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.

23. 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

24. ModelingHydropower generation in market context (GF level) Bid

25. 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

26. DesignRisk exposure revealed • Future risk—profile of financial instruments generating or losing income over time Present Past Future

27. 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.

28. 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.

29. 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)

30. 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

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