Wind Power Forecast Error Simulation Model

Abstract

One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Josip Vasilj

Associate Professor | Department of Power Grids and Substations

Researcher and Associate Professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses related to engineering economics, power system analysis, power grids and machine learning. His research focus is the application of advanced numerical methods to problems in the analysis and planning of power system operations.

Petar Sarajčev

Full Professor | Department of Power Grids and Substations

Damir Jakus

Full Professor | Department of Power Grids and Substations

Researcher and a full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split. His research interests include power system optimization and planning, RES integration, electricity market modeling.