Market-Based Two-Stage Stochastic Scheduling Programming Considering Demand Side Provider and Wind Power Penetration

The need for reserve provision in power systems is growing steadily due to the increase in wind power penetration level. This paper aimed to present a model for using demand side resources as flexible resources that are aggregated in a demand side provider (DSP). The DSP consists of aggregating demand side response resources as grid backup and energy storage systems as fast reserve. In this study, the incentive-based model of the capacity market program has used to achieve a certain level of demand side response. A two-stage stochastic programming model for energy and reserve determination in the unit commitment problem has presented in the form of mixed integer linear programming. The optimal variables of energy and reservation have obtained through two different perspectives, independent system operator (ISO) and risk-averse ISO. The conditional value at risk index has used as a risk measure to model ISO’s risk-averse behavior. On the other hand, the Weibull probability distribution function and the backward method have used to generate wind speed scenarios and reduce these scenarios, respectively. The results confirm that the simultaneous scheduling of energy resources and the demand side aggregator for energy and reserve provision, while reducing the impact of wind power uncertainty, leads to a reduction in the total cost of system operation.