Quantifying the value of improved wind energy forecasts in a pool-based electricity market

RENEWABLE ENERGY

卷:80

Article

Mc Garrigle, E. V.¹  Leahy, P. G.^1,2,3 

[1] Natl Univ Ireland Univ Coll Cork, Sch Engn, Cork, Ireland

[2] Natl Univ Ireland Univ Coll Cork, Environm Res Inst, Cork, Ireland

[3] Sci Fdn Ireland, Marine Renewable Energy Ireland MaREI Res Ctr, Dublin, Ireland

关键词: Wind forecasting;    Autoregressive moving average;    Stochastic unit commitment;    Wind curtailment;    Power systems;    Ireland;   

DOI  :  10.1016/j.renene.2015.02.023

来源: Elsevier

【 摘 要 】

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. (C) 2015 Elsevier Ltd. All rights reserved.

【 授权许可】

Free