Prediction of power fluctuations from wind power plants in Sri Lanka by an auto regressive model

Abstract

Hydropower is the major renewable energy contributor to the national grid in Srii Lanka amounting to 48% of the total installed capacity. Further expansion of hydropower however, is| limited due to environmental and resource constraints. Meanwhile the demand for electricity is'. estimated to rise at an annual rate of 8% - 10% prompting the need to find alternative power options.^ The wind energy has been identified as a promising candidate to generate electricity in Sri Lanka. v||| However for a reliable integration of wind energy, the volatile nature of wind has to be understood. ^ Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility |S| customers. Wind speed-time series data typically exhibit autocorrelation, which can be defined as the || degree of dependence on preceding values. This paper presents the state of the art wind power forecasting technique and examines the use of a standard class of statistical time-series models to fjj predict wind power output. Present study shows how an autoregressive model can serve as a ^ modelling and forecasting wind power generation in Puttalama area.