RATC Project – Data Requests from TVA for the Algorithm Team

1. RATC Project – Data Requests from TVA for the Algorithm Team August 2, 2012

2. Network Model

3. TVA Network Model • Dataset examples: PSS/E file, PowerWorld, ProMod, GridView, Plexos • Bus: • MW and MVAr load levels for each hour, each bus in the year (8760). • 5 minute loading level (MW and MVAr) for each bus for at least 1 typical day for each month (12 days) • Branch (line and transformer): • Bus connections • Thermal ratings (long-term, short-term, emergency ratings) • Stability ratings • Resistance, reactance, etc. • Transformer information (settings) • Purpose: to conduct economic dispatch, unit commitment, optimal power flow studies

4. Generator Information

5. Generator Information • Cost information: • Generator operating heat rate curves + fuel costs (or simply the operating cost curve) • Startup cost (cost or heat rate + fuel cost) • No-load cost (cost or heat rate + fuel cost) • Cycling and ramping information: • MW per minute ramp rate • Minimum up and down times • Generator parameters: • Bus location • Pmaxand Pmin (MW), Qmax and Qmin (MVAr) • Generator availability: • Maintenance schedule, number of weeks out of service • Hydro modeling and scheduling: • Hourly production schedule for each hydro plant • Dispatch availability (is the plant dispatchable or does the plant have a fixed output) • Pumped-storage • If TVA has pumped storage, we need to know the MWh capacity, the Pmax and Pmin production capability, and efficiency

6. RATC Algorithm Applications: Normal Operations

7. RATC Normal Operations • Generator information + Network model required to study: • Power flow and optimal power flow • Real-time economic dispatch • Hour-ahead dispatch • Day-ahead unit commitment planning Generator + Network Information Day-ahead UC/Hour-ahead Dispatch RATC Algorithm

8. RATC Algorithm Applications: Emergency Operations

9. RATC Emergency Operations • Generator information + Network model required to study: • Real-time corrective topology control applications • Prevent load shedding • Enhance re-dispatch capability • N-m events • Minimize load shedding • Faster system recovery procedure • Malicious attacks • Minimize load shedding • Faster system recovery procedure

10. Real-time corrective topology control applications Example of the RATC Algorithm Required information to obtain system condition

11. Real-time corrective topology control applications Example of the RATC Algorithm Required information to obtain system condition Static information: network model + generator information Dynamic information: current network state (bus voltage, angles, line flows, line status) generator information (dispatch, availability, ramping capacity)

12. Testing of RATC Algorithm for Real-time Corrective Applications • Step 1: Static Data • Use static data and create N-1, N-m, and sudden drop of renewables events • Simulation RATC algorithm response • Step 2: Dynamic Data • Collect TVA historical information on past contingency events • Simulate TVA’s corrective response without RATC • Simulate RATC algorithm response