GADS and LOLE Considerations in Gas- Electric Coordination. ENGCTF June 13, 2013

Transcription

1 GADS and LOLE Considerations in Gas- Electric Coordination ENGCTF June 13, 2013

2 Generating Availability Data System (GADS) National database of electric generator performance, produced by the North American Electric Reliability Corporation (NERC) Historical data on 5,900 generators (78%) of US and Canadian fleet Mandatory reporting for all conventional generation >20 MW Typically, asset owners submit to MISO via PowerGADS and to NERC via WebE-GADS Data complied annually; presented for 5 individual years and for 5-year average Data reported on individual unit Design, Performance, and Events 1

3 Loss of Load Expectation (LOLE) Studies at MISO In accordance with the MISO Tariff, the reliability objective of an LOLE study is to determine a minimum Planning Reserve Margin (PRM) that would result in the MISO system experiencing a less than one day loss of load event every 10 years PRMs provide resource cushion to ensure system reliability Load Serving Entities (LSEs) must meet a Planning Reserve Margin and a Local Clearing Requirement based on their Local Resource Zone LOLE analysis accounts for forced outage rates, planned outages, forecast uncertainty, etc. Many inputs for LOLE analysis are derived from GADS 2

4 GADS Event Classifications IEEE Standard 762 defines Active and Inactive States Inactive unit is unavailable for service for an extended period of time for reasons not related to equipment Inactive State Code Description Inactive Reserve IR the unit isn t available for service but could be brought back into service in days, with some repairs Mothballed MB the unit isn t available for service but could be brought back into service in weeks to months, with some repairs Retired RU the unit isn t available for service and is not expected to return to service in the future 3

5 GADS Event Classifications Active States include Outages - unit is not synchronized to the grid system and not in a Reserve Shutdown state Outage Type Code # Outage Characteristics Planned PO Scheduled well in advance; predetermined duration; lasts for several weeks Maintenance MO Can occur any time during the year; has a flexible start date; may or may not have predetermined duration; usually much shorter than a PO Startup Failure SF Occurs when unit is unable to synchronize within a specified startup following an outage or Reserve Shutdown Unplanned (Forced) - Immediate U1 Requires immediate removal of a unit from service, another Outage State or a Reserve Shutdown state; usually results from immediate mechanical/electrical/hydraulic control systems trips and operatorinitiated trips in response to unit alarms Unplanned (Forced) - Delayed U2 Requires removal of unit from the in-service state within 6 hours Unplanned (Forced) - Postponed U3 Requires removal of unit from the in-service state before the end of the next weekend 4

6 GADS Event Classifications Active States also include Reserve Shutdown - unit is available for load but is not synchronized due to lack of demand; economic outage Lack of Fuel Event Code # Description Lack of Fuel (OMC) 9130 Lack of fuel (water from rivers or lakes, coal mines, gas lines, etc.) where the operator is not in control of contracts, supply lines, or delivery of fuels Lack of Fuel 9131 Lack of fuel (interruptible supply of fuel part of fuel contract); If the operator elected to contract for fuels where the fuel (for example, natural gas) can be interrupted so that the fuel suppliers can sell the fuels to others (part of the plant fuel cost-saving measure), then the lack of fuel is under management control and is not applicable to this case. 5

7 LOLE Analysis Inputs and GADS Definitions Historic unit performance data from GADS used for LOLE analysis includes: Planned maintenance data (average number of events and duration) Generation verification test capability (GVTC) Monthly maximum output profile (net dependable capacity) Unit Forced Outage Rates Forced outage rate (FOR): A measure of the probability that a generating unit will not be available due to forced outages. Attaching the term equivalent to any rate or factor, e.g. equivalent forced outage rate (EFOR), indicates that both full outages and de-ratings have been considered in the calculation. The term demand applied to a rate, e.g. EFORd, indicates that the probability of an occurrence has been estimated for periods when the unit is in demand to generate. 6

8 GADS & LOLE Analysis Eq. 1 EFORd = (FOHd + EFDHd) / (SH + FOHd) EFORd = Equivalent Forced Outage Rate Demand FOHd = Forced Outage Hours Demand EFDHd = Equivalent Forced De-rated Hours Demand SH = Service Hours; the hours the unit is available for operation on an annual basis EFORd = Equivalent Forced Outage Rate Demand; a measure of the probability that a generating unit will not be available due to forced outages or forced de-ratings when there is demand on the unit to generate XEFORd = EFORd excluding causes of outages that are Outside Management Control (OMC) 7

9 GADS & LOLE Analysis Cont. Eq. 1 EFORd = (FOHd + EFDHd) / (SH + FOHd) Reserve Shutdown events count against Service Hours. Forced outages add to FOHd. Derates add to EFDHd. More time in Reserve Shutdown means fewer Service hours, and this translates to an increased impact on EFORd should an outage occur (OMC) Lack of Fuel events count against Service Hours but do not add to Forced Outages Lack of Fuel events count against Service Hours and add to Forced Outages. 8

10 Considerations EFORd is used in LOLE simulations to model unit forced outage rates. XEFORd (OMC events excluded) is used to determine the unforced capacity (UCAP) rating of each unit and summed per MISO zone to calculate the total UCAP megawatts, which is used in the PRM UCAP calculation. PRM UCAP feeds into the determination of the Planning Reserve Margin Requirement. 9

11 Considerations cont. Each Load Serving Entity has an obligation to meet Planning Reserve Margin Resource Requirements; if the LSE does not have enough capacity resources to meet its Requirement, it will have to procure (pay for) additional capacity resources. Capacity resources will receive payment commensurate with their ability to generate when dispatched, and the Forced Outage Rate serves as an input to the quantification of this ability. A higher Forced Outage Rate translates to lost earning potential in MISO s capacity market (capacity auction). 10

12 Considerations cont. Generators designated as Planning Resources are required to submit an offer into MISO s Day Ahead (DA) Energy Market unless they are on a scheduled outage. If a unit is selected through the Day Ahead process, it is obligated to run in Real Time. Units on Reserve Shutdown are considered on outage for this purpose and are not required to offer into DA. 11

13 Discussion Points MISO s current LOLE study methodology relies heavily upon GADS. A fundamental shift in unit performance will be reflected in GADS, over time. While the GADS Reserve Shutdown status offers cost savings for units that are not needed to meet demand and/or cannot be economically dispatched, it potentially also masks inability of resources to respond to a dispatch call from MISO. The extent to which GADS captures fuel risk impacts the extent to which MISO s LOLE analysis captures fuel risk. 12

14 Links NERC Generating Availability Data System Data Reporting Instructions 20GADS%20Data%20Reporting%20Instructions%20Effective%20Janu ary%201,% pdf IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity System%20Working%20Group/IEEE% %20Task%20Force%20(IEEE762TF)/ pdf MISO s 2013 LOLE Study Report OLE%20Study%20Report.pdf 13

15 APPENDIX 14

16 MISO GADS Data for Lack of Fuel Events for Gas Units Cause Codes # of Times Used Duration (Hrs) Duration (EQ Hrs) Reduction (Avg MW) Loss (MWh) ,584 6, , ,786 1, ,097 15

17 NERC Recommendations for Future GADS Analysis Recommendations from 2013 NERC Report Special Reliability Assessment: Accommodating an Increased Dependence on Natural Gas for Electric Power ( NAL.pdf) include: Perform deeper dive analysis to a sample of individual generator outages to determine the cause of the outage. GADS should be able to identify if generator outages were the result of either fuel contract interruptions or uncontrolled gas curtailment events. Overlay GADS outage data on pipeline capacity trends to determine if there is a correlation and identify potential leading indicators. Determine natural gas pipeline and supply conditions during times of gas generator outages. Perform a study to determine approaches where dispatch trends and load duration curves can provide insights to future generator performance. Use GADS data for probabilistic adequacy models and develop scenarios around increased forced outage rates 16