Energy meteorology for accurate forecasting of PV power output on different time horizons

被引:19
|
作者
Reindl, Thomas [1 ]
Walsh, Wilfred [1 ]
Zhan Yanqin [1 ]
Bieri, Monika [1 ]
机构
[1] NUS, SERIS, 7 Engn Dr 1, Singapore 117574, Singapore
关键词
Solar photovoltaic systems; energy meteorology; power generation forecasts; economic value;
D O I
10.1016/j.egypro.2017.09.415
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Energy meteorology is a new discipline whose importance derives from the need for variable, non-dispatchable renewable power generation to be quantified on timescales from decades (resource assessment) down to minutes ("now-casting"). The need for power generation forecasts becomes more apparent as the variable generation fraction increases above a few percent at this level sudden large changes in generation capacity ("ramp rates") can affect power quality and even lead to grid instability. For this reason, many jurisdictions worldwide are starting to implement forecasting requirements on solar photovoltaic (PV) plant owners, including China where the national standard GB/T 19964-2012 on "Technical requirements for connecting photovoltaic power stations to power systems" asks for 15-minute to day-ahead forecasts. Failure to do so or inaccurate predictions, i.e. outside of a desired corridor (10-15%) lead to penalties in form of reduced reimbursements for the provided solar power. PV power output forecasting errors can arise not only from predicting irradiance, but also- and this is widely underestimated- from the conversion of irradiance to actual PV power generation. Additional uncertainties of 10% during this step are not uncommon. In this paper, the economic value of forecasting is evaluated using a case study from Henan province, China. We show that even minor deviations from the requested forecasting frequency and prediction corridor can result in revenue losses that have direct impact on the financials of the project (i.e., discounted payback period, net-present value and internal rate of return). This will spark a growing need for accurate energy meteorology in the future. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:130 / 138
页数:9
相关论文
共 50 条
  • [41] Power Output Forecasting of a Solar House by Considering Different Cell Temperature Methods
    Ayvazogluyuksel, Ozge
    Filik, Ummuhan Basaran
    2017 10TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO), 2017, : 1253 - 1257
  • [42] Forecasting intraday power output by a set of PV systems using recurrent neural networks and physical covariates
    Pierrick Bruneau
    David Fiorelli
    Christian Braun
    Daniel Koster
    Neural Computing and Applications, 2024, 36 (31) : 19515 - 19529
  • [43] Forecasting power output of PV grid connected system in Thailand without using solar radiation measurement
    Chupong, Charnon
    Plangklang, Boonyang
    9TH ECO-ENERGY AND MATERIALS SCIENCE AND ENGINEERING SYMPOSIUM, 2011, 9
  • [44] Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons
    Fabrizio De Caro
    Jacopo De Stefani
    Gianluca Bontempi
    Alfredo Vaccaro
    Domenico Villacci
    Technology and Economics of Smart Grids and Sustainable Energy, 5
  • [45] Robust Assessment of Short-Term Wind Power Forecasting Models on Multiple Time Horizons
    De Caro, Fabrizio
    De Stefani, Jacopo
    Bontempi, Gianluca
    Vaccaro, Alfredo
    Villacci, Domenico
    TECHNOLOGY AND ECONOMICS OF SMART GRIDS AND SUSTAINABLE ENERGY, 2020, 5 (01):
  • [46] Plus Energy Building Flexibility: Impact of BESS Control Strategy and PV Power Forecasting
    Barchi, Grazia
    Dalla Maria, Enrico
    Pierro, Marco
    Belleri, Annamaria
    2024 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES, SEST 2024, 2024,
  • [47] A Machine Learning Model Ensemble for Mixed Power Load Forecasting across Multiple Time Horizons
    Giamarelos, Nikolaos
    Papadimitrakis, Myron
    Stogiannos, Marios
    Zois, Elias N.
    Livanos, Nikolaos-Antonios I.
    Alexandridis, Alex
    SENSORS, 2023, 23 (12)
  • [48] A Novel Approach to Improve Power Output of PV Array Under Different Shading Conditions
    Sahu, Himanshu Sekhar
    Nayak, Sisir Kumar
    2014 6TH IEEE POWER INDIA INTERNATIONAL CONFERENCE (PIICON), 2014,
  • [49] Dual Output Power Management Unit for a PV-Battery Hybrid Energy System
    Rezk, Ahmed A.
    Helmy, Amr
    Ismail, Yehea
    2015 5TH INTERNATIONAL CONFERENCE ON ENERGY AWARE COMPUTING SYSTEMS & APPLICATIONS (ICEAC), 2015,
  • [50] Estimation of PV output power in moving and rocking hybrid energy. marine ships
    Liu, Hongda
    Zhang, Qing
    Qi, Xiaoxia
    Han, Yang
    Lu, Fang
    APPLIED ENERGY, 2017, 204 : 362 - 372