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State Estimator (SE) and Simultaneous Feasibility Test (SFT) Status Report

Progress in reducing generation and load disparities, improving observability, and addressing data/model issues. Plans to integrate SE and SFT into real-time operations for more accurate analysis and congestion management. Expected implementation by April 1.

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State Estimator (SE) and Simultaneous Feasibility Test (SFT) Status Report

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  1. State Estimator (SE)andSimultaneous Feasibility Test (SFT)Status Report Steve Myers Manager of System Operations

  2. State Estimator • Progress • Total difference between generation & load reduced from 10’s of 1000’s at first to <500 MW • Approximately 25 buses >50 MW mismatch • 90% observability (75% with measurements)

  3. Uses of the State Estimator • Identifying data problems • Identifying model problems • Monitoring of locations w/o SCADA (by System Operators) • Creating a case for Contingency Analysis • Normally successful at least once per day

  4. SE Plan • Continue to incrementally improve • Continue to reduce mismatches • With Engineer’s attention, use in Day-Ahead analysis • Train System Operators • Ultimately – SE will run CA in RT sequence

  5. SE Plan • Needs • Data Response from QSE’s and Private Networks • Unit Status – QSE • Private Network Issues to Correct • Net Gen sent as one unit • Loads not modeled • Data required by ERCOT Operating Guides Section 8

  6. Simultaneous Feasibility Test (SFT) • Calculates “Shift Factors” used in Congestion Management • Progress • Attempted use in December '02 • Bugs that had not shown up in test mode • Waiting on fixes from vendor • Once offline testing complete, will test again in production

  7. SFT Plan • Use in Day-Ahead • Initially peak hour • Limited contingencies • Use in Hours Ahead • Initially test mode • Limited contingencies • Limited iterations with SPD

  8. Next Steps • Contingency Analysis will run in the Real-Time sequence and upon demand • SE and SFT will run for each BES deployment • ERCOT expects its systems to be ready By April 1

  9. What Do We Gain? • More accurate analyses – closer to RT • Greatly improved pro-active CM • Much more accurate “Shift Factors” • Potentially less OOM deployments

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