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Time Series Analysis using Vector Autoregressive Model of Wind Speeds in Bangui Bay and Selected Weather Variables in Laoag City Philippines

Author

Listed:
  • Cherie ORPIA

    (Mariano Marcos State University)

  • Dennis MAPA

    (University of the Philippines School of Statistics)

  • Julius ORPIA

    (SN Aboitiz Power Magat Inc)

Abstract

Wind energy is the fastest growing renewable energy technology Wind turbines do not produce any form of pollution Moreover when strategically positioned the wind turbines blend with the area s natural landscape In the long run the cost of electricity using wind turbines is cheaper than conventional power plants since it does not consume fossil fuel Wind speed modeling and forecasting are important in the wind energy industry starting from the feasibility stage to actual operation Forecasting wind speed is vital in the decision making process related to wind turbine sizes revenues maintenance scheduling and actual operational control systems This paper uses econometric models to forecast the wind speeds of turbines in the Northwind Bangui Bay wind farm located in the Province of IlocosNorte Philippines using the Vector Auto Regressive VAR model The explanatory variables used are local wind speed humidity temperature and pressure generated from the meteorological station in Laoag City Province of IlocosNorte Philippines The use of VAR model using daily time series data reveals that wind speeds of the turbines can be explained by the past wind speed the wind speed in Laoag City humidity temperature and pressure Results of the analysis using the forecast error variance decomposition show that wind speed in Laoag City temperature and humidity are important determinants of the wind speeds of the turbines

Suggested Citation

  • Cherie ORPIA & Dennis MAPA & Julius ORPIA, 2014. "Time Series Analysis using Vector Autoregressive Model of Wind Speeds in Bangui Bay and Selected Weather Variables in Laoag City Philippines," Journal of Advanced Research in Management, ASERS Publishing, vol. 5(1), pages 52-62.
  • Handle: RePEc:srs:jemt00:v:5:y:2014:i:1:p:52-62
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