Simulation of transcontinental wind and solar PV generation time series

被引：40
作者：
Nuno, Edgar [1 ]
Maule, Petr [1 ]
Hahmann, Andrea [1 ]
Cutululis, Nicolaos [1 ]
Sorensen, Poul [1 ]
Karagali, Ioanna [1 ]
机构：
[1] Tech Univ Denmark, Dept Wind Energy, Roskilde, Denmark
来源：
RENEWABLE ENERGY | 2018年 / 118卷
关键词：
Large-scale integration; Renewable energy sources; Solar power; Wind power; POWER; MODEL;
D O I：
10.1016/j.renene.2017.11.039
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
The deployment of Renewable Energy Sources (RES) is driving modern power systems towards a fundamental green transition. In this regard, there is a need to develop models to accurately capture the variability of wind and solar photovoltaic (PV) power, at different geographical and temporal scales. This paper presents a general methodology based on meteorological reanalysis techniques allowing to simulate aggregated RES time series over large geographical areas. It also introduces a novel PV conversion approach based on aggregated power curves in order to capture the uncertainty associated to the technical characteristics of individual installations spread across large regions. The proposed methodology is validated using actual power data in Europe and can be applied to represent intermittent generation in network development plans, reliability and market studies, as well as operational guidelines. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码：425 / 436
页数：12
相关论文
共 23 条
  • [1] A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns
    Cradden, Lucy C.
    McDermott, Frank
    Zubiate, Laura
    Sweeney, Conor
    O'Malley, Mark
    [J]. RENEWABLE ENERGY, 2017, 106 : 165 - 176
  • [2] Cutululis N. A., 2012, TECH REP
  • [3] The ERA-Interim reanalysis: configuration and performance of the data assimilation system
    Dee, D. P.
    Uppala, S. M.
    Simmons, A. J.
    Berrisford, P.
    Poli, P.
    Kobayashi, S.
    Andrae, U.
    Balmaseda, M. A.
    Balsamo, G.
    Bauer, P.
    Bechtold, P.
    Beljaars, A. C. M.
    van de Berg, L.
    Bidlot, J.
    Bormann, N.
    Delsol, C.
    Dragani, R.
    Fuentes, M.
    Geer, A. J.
    Haimberger, L.
    Healy, S. B.
    Hersbach, H.
    Holm, E. V.
    Isaksen, L.
    Kallberg, P.
    Koehler, M.
    Matricardi, M.
    McNally, A. P.
    Monge-Sanz, B. M.
    Morcrette, J. -J.
    Park, B. -K.
    Peubey, C.
    de Rosnay, P.
    Tavolato, C.
    Thepaut, J. -N.
    Vitart, F.
    [J]. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2011, 137 (656) : 553 - 597
  • [4] Hahmann A.N., 2015, DTU WIND ENERGY, V50, P80
  • [5] Wind climate estimation using WRF model output: method and model sensitivities over the sea
    Hahmann, Andrea N.
    Vincent, Claire L.
    Pena, Alfredo
    Lange, Julia
    Hasager, Charlotte B.
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2015, 35 (12) : 3422 - 3439
  • [6] A Reanalysis System for the Generation of Mesoscale Climatographies
    Hahmann, Andrea N.
    Rostkier-Edelstein, Dorita
    Warner, Thomas T.
    Vandenberghe, Francois
    Liu, Yubao
    Babarsky, Richard
    Swerdlin, Scott P.
    [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2010, 49 (05) : 954 - 972
  • [7] Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum
    Huld, Thomas
    Amillo, Ana M. Gracia
    [J]. ENERGIES, 2015, 8 (06): : 5159 - 5181
  • [8] Jimenez P., 2015, B AM METEOROL SOC, V12, P2015, DOI DOI 10.1175/BAMS-D-14-00279.1
  • [9] King D. L., 2004, PHOTOVOLTAIC ARRAY P, DOI DOI 10.2172/919131
  • [10] King D. L., 2007, TECH REP
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