Application of system identification modelling to solar hybrid systems for predicting radiation, temperature and load

被引：4
|
作者：
Sinha, S
Kumar, S
Matsumoto, T
Kojima, T
机构：
[1] Seikei Univ, Fac Engn, Dept Ind Chem, Tokyo 1808633, Japan
[2] Kyoto Univ, Dept Global Environm Eng, Sakyo Ku, Kyoto 60601, Japan
来源：
RENEWABLE ENERGY | 2001年 / 22卷 / 1-3期
关键词：
Mathematical models - Parameter estimation - Regression analysis - Solar radiation - Temperature - Thermal load;
D O I：
10.1016/S0960-1481(00)00034-3
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Uncertainties in local solar radiation, ambient temperature and thermal load data have been one of the major factors limiting the reliability and efficiency of solar thermal hybrid systems. In the present paper, moving average auto regressive exogenous (ARX) model based reasoning has been mooted and modified to include moving average method, as an effective tool for predictions of these data. The results show that the method is quite robust and is capable of predicting fairly accurate results, which would make these systems more viable in areas where meteorological data are not available or vague. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：281 / 286
页数：6
相关论文
共 50 条
  • [1] Application of system identification modelling to solar hybrid systems for predicting radiation, temperature and load
    Sinha, S
    Kumar, S
    Matsumoto, T
    Kojima, T
    RENEWABLE ENERGY: TECHNOLOGIES & POLICIES FOR SUSTAINABLE DEVELOPMENT, 1999, : 489 - 492
  • [2] MA system identification using higher order cumulants application to modelling solar radiation
    Safi, S
    Zeroual, A
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2002, 72 (07) : 533 - 548
  • [3] Space weather modelling with intelligent hybrid systems: Predicting the solar wind velocity
    Wintoft, P
    Lundstedt, H
    SOLAR-TERRESTRIAL RELATIONS: PREDICTING THE EFFECTS ON THE NEAR- EARTH ENVIRONMENT, 1998, 22 (01): : 59 - 62
  • [4] A hybrid modelling approach for assessing solar radiation
    Shamim, M. A.
    Bray, M.
    Remesan, R.
    Han, D.
    THEORETICAL AND APPLIED CLIMATOLOGY, 2015, 122 (3-4) : 403 - 420
  • [5] A hybrid modelling approach for assessing solar radiation
    M. A. Shamim
    M. Bray
    R. Remesan
    D. Han
    Theoretical and Applied Climatology, 2015, 122 : 403 - 420
  • [6] System for load modelling in power systems
    Ju, Ping
    Li, Defeng
    Lu, Xiaotao
    Dianli Xitong Zidonghue/Automation of Electric Power Systems, 1998, 22 (06):
  • [7] A stochastic framework for hybrid system identification with application to neurophysiological systems
    Hudson, Nicolas
    Burdick, Joel
    HYBRID SYSTEMS: COMPUTATION AND CONTROL, PROCEEDINGS, 2007, 4416 : 273 - +
  • [8] Application of Neural Networks Solar Radiation Prediction for Hybrid Renewable Energy Systems
    Chatziagorakis, P.
    Elmasides, C.
    Sirakoulis, G. Ch.
    Karafyllidis, I.
    Andreadis, I.
    Georgoulas, N.
    Giaouris, D.
    Papadopoulos, A. I.
    Ziogou, C.
    Ipsakis, D.
    Papadopoulou, S.
    Seferlis, P.
    Stergiopoulos, F.
    Voutetakis, S.
    ENGINEERING APPLICATIONS OF NEURAL NETWORKS (EANN 2014), 2014, 459 : 133 - 144
  • [9] Solar radiation modelling for the simulation of photovoltaic systems
    Mondol, Jayanta Deb
    Yohanis, Yigzaw G.
    Norton, Brian
    RENEWABLE ENERGY, 2008, 33 (05) : 1109 - 1120
  • [10] Predicting solar radiation fluxes for solar energy system applications
    Saffaripour, M. H.
    Mehrabian, M. A.
    Bazargan, H.
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2013, 10 (04) : 761 - 768
12345