Discrete forecast error scenarios methodology for grid reliabitity assessment in short-term planning

Abstract

With the increasing amount of renewable and difficult-to-forecast generation units, Transmission System Operators (TSO) are facing new challenges to operate the grid properly. Indeed, given the intrinsic variability and limited predictability of most renewable generations, the application of the conventional and deterministic N-1 method becomes very costly. Therefore, a new approach is needed for system operational planning. This paper presents a method that combines the advantages of probabilistic and deterministic approaches in order to estimate risk indicators while considering errors on weather (hence generation) forecasts, uncertainties on loads and timing constraints of the decision-making process in operational planning. This decision support method provides the planner with indicators to analyze, improve and finally, validate a grid plan. The method has been tested and its results have been compared with the classical N-1 analysis. Results show that the method offers more indicators to help the planner and to compare different grid plans.