Nitin Anand Shrivastava

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Accurate forecasting of streamflows has been one of the most important issues as it plays a key role in allotment of water resources. However, the information of streamflow presents a challenging situation; the streamflow forecasting involves a rather complex nonlinear data pattern. In the recent years, the support vector machine has been used widely to(More)
Accurate electricity price forecasting is a formidable challenge for market participants and managers owing to high volatility of the electricity prices. Price forecasting is also the most important management goal for market participants since it forms the basis of maximizing profits. This study investigates the performance of a novel neural network(More)
Forecasting electricity prices has been a widely investigated research issue in the deregulated power market scenario. High price volatilities, price spikes caused by a number of factors such as weather uncertainty, fluctuating fuel prices, transmission bottlenecks, etc., make the task of accurate price forecasting a formidable challenge for the market(More)
Classifying the wind power ramp events. Accurate prediction of wind ramp events is critical for the ensuring the reliability and stability of the power systems with high penetration of wind energy. This paper proposes a classification based approach for estimating the future class of wind ramp event based on certain thresholds. A parallelized gradient(More)
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