Electric Power Expo 2015
Session 1E: Asset Optimization
Wednesday, April 22 1:45 PM - 3:45 PM
Integ will be presenting: Understanding the True Cost of a Unit’s Unavailability and the True Value of its Commercial Availability
Authors: Wing Cheng & John Basiak
Click to register
Click to add to your calendar
It is now recognized by many experts that the traditional NERC GADS generator reliability rates and factors do not adequately reflect the complexity of today’s market condition. EAF, EUOR, EFORd and such do not accurately measure the localized demand variability embedded in the Locational Marginal Pricing of energy. Key questions about the profitability of being available and the economic losses of being unavailable are not answered. Commercial Availability (CA) is emerging to be a better indicator of Generator Reliability and Performance when economic impact is attached to them. This presentation will outline the relationship between the actual margin and lost margins when a generator experiences an outage or derate. By evaluating the heat curves, the incremental cost curves, the startup costs, and unit operating constraints against the hourly LMP or system Lambda tied to each specific unit, energy producers will be able to better determine the true economic impact of each unit outage or derate. With the advent of computing power and the availability of robust market data published by each ISO, detail hourly analysis can now be performed to bestow us insight into the complex relationship between economic dispatch target, actual generation, available capacity, energy and ancillary services revenues, generation costs, startup costs and no-load cost. Ultimately the CA percentage tells us how much total profit we would have made and how much lost opportunity dollars we left on the table due to inopportune outages and derates.
With this new insight, incentives become clearer when considering maintenance outages during lower priced periods in order to capture the maximum potential margin when the unit is dispatched during peak demand periods. Utilities should have the capability to determine how much margin the unit could have made by simulating a generation pattern if the event was avoided. The analysis of key drivers affecting plant profitability will aid in focusing efforts on having generators available to generate when profit potential is high.