Peer-Reviewed Journal Details
Mandatory Fields
McGarrigle, Edward V.; Leahy, Paul G.
Renewable Energy
Quantifying the value of improved wind energy forecasts in a pool-based electricity market
Optional Fields
Wind forecast Unit commitment Economic dispatch PLEXOS Autoregressive moving average Curtailment Stochastic scheduling
This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.
Grant Details
Irish Research Council
Embark Scholarship