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To improve forecasting accuracy for baseline load and load impact from demand response resources, this paper develops three innovative statistical models. These models are regression spline fixed effect model, fixed effect change point model and mixed effect change point model. The models developed are applied to forecast baseline load and load impact from air conditioning cycling demand response...
As a type of clean and renewable energy source, wind power is being widely used all around the world. However, owing to the uncertainty and instability of the wind power, it is important to build an accurate prediction model for wind power for the grid-connected security operation. The performance of hybrid method is always better than that of single ones in the wind power prediction. Actual wind...
One of the most effective and cheapest strategies to integrate the fast-increasing number of solar-based generators is by forecasting their power output to schedule power dispatch, energy storages, manage backup generators, and compensate for any fluctuations of solar power. In particular, forecasting the insolation is invaluable to predict the power generated by photovoltaic arrays. An essential...
Electric utilities have been using wind power to an increasing extent in order to provide clean energy. However, this resource depends on the intermittency of wind, and this makes balancing supply and demand challenging for the system operator. In this paper we propose a downscaling approach yielding daily probabilistic wind speed scenarios for the turbine hub height, thus making them useful for generating...
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