Assessment of the benefits from advanced load & wind power forecasting in autonomous power systems
Résumé
In this paper, a methodology is developed to assess the benefits from the use of advanced wind power and load forecasting techniques for the scheduling of a medium or large size autonomous power system. The power system scheduling is optimised through a genetic algorithm based unit commitment model that simulates in detail start-up/shut-down procedures of the power units, ramp constraints, generation limits etc. Different types of forecasts are considered as input to the unit commitment model and the operation costs are estimated for each case. Emphasis is given to define appropriate simple forecasting models that can be used on-line. The performance of these models is used as reference to evaluate advanced techniques. The case-study of the Greek island of Crete is examined. A simple model is developed to explain in an intuitive way how the power system structure might attenuate the effect of inaccuracy in forecasts. Finally, the impact of forecasting accuracy on the various power system management functions is discussed.
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