Hybrid Stochastic Short-Term Models for Wind and Solar Energy Trajectories

In the presence of renewable energy resources in the power system, most grid management applications make use of hourly or even minutely models for solar irradiance and wind speed. However, studies on the grid impact and controllability of these resources sometimes require focusing on shorter duration timeframes, namely secondly to minutely models. Detailed studies on power and voltage quality impacts, dynamic stability analysis, and transient capabilities of controllers are among those that can benefit from such short-term models. This paper presents a new method of creating random solar and wind samples, which utilizes a short-term (secondly to minutely) component and a longer-term component in order to capture both the overall statistical description of the energy resource, as well as the time-correlated values observed in wind speed and solar irradiance data sets. Models developed in this paper can generate wind and solar energy trajectories at very high resolutions to be used in suitable system-level studies.