Stochastic analysis of wind energy uncertainty impact on ISO risk-taking in joint energy and reserve markets using conditional value at risk

Abstract

Uncertainty management of the large scale wind power resources is mainly known as one of the most challenging aspects in future electricity market operations, where network operation may put at risk due to the wind power forecasting errors. Therefore, it is necessary to evaluate the impact of the wind power uncertainty on the operator risk-taking by using validated tools. This paper proposes a new mixed integer linear programming model for joint energy and reserve market clearing taking into account the co-optimization of the market clearing and operation cost of the thermal units. Also, wind power uncertainty is handled by means of two-stage stochastic programming and risk concept is introduced and formulated via a well-known measure to account for operator risk taking level. The proposed model is formulated as a two-stage stochastic programming where it clears the joint energy and reserve markets considering different penetration and forecasting accuracy levels of the wind power. Furthermore, supplementary terms are added to the objective function and constraints of the problem in order to measure the risk related to the wind power uncertainty.