Peer-Reviewed Journal Details
Mandatory Fields
McGarrigle, Edward V.; Leahy, Paul G.
2015
August
Renewable Energy
Quantifying the value of improved wind energy forecasts in a pool-based electricity market
Published
()
Optional Fields
Wind forecast Unit commitment Economic dispatch PLEXOS Autoregressive moving average Curtailment Stochastic scheduling
80
8
517
524
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.
0960-1481
10.1016/j.renene.2015.02.023
Grant Details
Irish Research Council
Embark Scholarship