Supporting ARPA -E Competition on Optimal Power Flow · Selecting Optimization Problem ‣...
Transcript of Supporting ARPA -E Competition on Optimal Power Flow · Selecting Optimization Problem ‣...
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Supporting ARPA-E Competition on Optimal Power Flow
PNNL – Feng Pan, Stephen Elbert UW-Madison – Christopher DeMarco ASU – Hans Mittelmann
March 30, 2016
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Optimal Power Flow Competition
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Support Team and Competition Components
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DEEP Support – Design, Execute, Evaluate and Promote
– Optimization problem – Data sets – Competition platform
• Website • Back-end server and evaluation system • Hardware
– Evaluation procedure and scoring metrics
– Resources • Solvers, programming languages, forum
– Outreach
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Open Competition
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‣ Open to everyone – Almost everyone
‣ Open formulation – Up to competitors to formulate the problem
‣ Open data sets – Release hidden data sets after announcing winner – Yes, we can handle proprietary data
‣ Open discussion – Communication through forum
‣ Open to suggestions and feedback – To release RFI
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Selecting Optimization Problem ‣ Selection criteria – industry relevance, reasonable learning curve for
general participants, specific and broad impact on applications, problem assumptions.
‣ Security-constraint is a must. ‣ Potential problems
– SCOPF + participation factor/droop. A two stage problem with additional state variables for each contingency.
– SCOPF + redispatch. It becomes a two stage problem with additional control variables (generation dispatch) for each contingency.
– SCOPF + demand flexibility – SCOPF with added discrete controls: transformer taps, switching capacitors
and reactors, phase shifter actions (likely drastically increase run time and will require different approaches.)
– Stochastic SCOPF with added scenarios and their probabilities. ‣ Need your inputs … ‣ We selected SCOPF with participation factor as the starting problem and
a starting point for discussion.
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Optimization Problem
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Security constrained optimal power flow with participation factor
Minimize total dispatch cost
power flow balance system limit
Open formulation, solutions will be verified through forward evaluation
Objective
Base-case
Contingency case power flow balance system limit
voltage set point droop control
Subject to
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SCOPF-PF
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Power-voltage polar coordinate formulation as an illustration
Base Case
Flow Balance
Power Flow on (i,j)
System Limits
Generation Cost
Contingencies
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SCOPF-PF
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Fixed voltage when reactive power within limit. PV->PQ
Active power adjustment with Participation Factor
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Data Sets
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‣ Three types – Training data for developing algorithms – Public data for monitoring progress (leaderboard) – Hidden data (will be made public afterwards) for final award
scoring ‣ Each data set will include these elements
– System model: power system description – Scenario: realization of exogenous variables, e.g., instantaneous
demand, generator data (cost, capacity and participation factor), line availability, …
– Contingency list ‣ Data format
– Current: PSS/E RAW and CSV – Other suggestions?
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Data Sources and Coordination ‣ RTS96 (UW-Madison) ‣ Small system (~100 buses), medium system (X100-X1,000
buses), large system (X10,000 buses) ‣ Coordinate with GRID DATA teams
– Format – Phased supply of data sets – What to include in a data set – Feasibility check - whether there exists a feasible solution to
SCOPF ‣ Coordination
– Suggestions on timeline, format, transfer method, feedback method?
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Evaluation
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‣ Output of an algorithm run will include two files: – competitor's solution file – system file, including computation time.
‣ Solution file – Competitor is required to output solution to specified variables
in a standard format – For example, objective value, generation dispatches, state
variables in power-voltage polar coordinates (p,q,v,θ) for the base case and all contingency cases.
‣ Forward evaluation – Check each constraint in a standard formulation and each
limit. – Calculate the total cost. – Record violation.
‣ Elapsed Time of entire run captured by system
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Scoring
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‣ Goal is to evaluate quality of an algorithm while preventing gaming
– Transparent – Clear – Easy to understand
‣ Three main metrics – Time – Objective value – Constraint violations
‣ Evaluation and scoring is generally an automatic process. Human-in-the-loop process is reserved for a small number of cases.
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Automated Evaluation and Scoring
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CEES – compile, execute, evaluate and score
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Interface with Participants
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‣ Participants will participate this competition through the competition platform (to be introduced next)
‣ Through the platform, participants can – Download data sets. – Submit algorithms to be evaluated and scored during the training
stage. – Use standardized input and output files. – Receive log file showing algorithm performance. – Make requests. – Discuss with the support team and other competitors.
‣ The platform is for evaluation and NOT a development environment.
‣ It is important to have sufficient data sets for participants to understand their algorithm performance and leave out surprises.
‣ The platform is a fair playground – same resource, same software version, and same environment.
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Participation Modes
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‣ Competitor – individuals and teams
‣ Industry sponsors – support competitor, provide data sets
‣ Contributor/sponsor – provide supporting materials and licensed software, join forum discussion
– CPLEX – Gurobi – Knitro – Xpressmp
– MATLAB & MATPOWER – GAMS – …more to come
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Questions and Suggestions?
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