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Coordinated Scheduling of Demand Response Aggregators and Customers in an Uncertain Environment

In this paper, a methodology to offer new potential of DR in real-time is presented. Since customers likely have extra possibilities for demand response (DR) participation in real-time, in addition to their scheduled potential in day-ahead, this method helps to provide balance in real-time market via DR aggregators. It can be vital once the stochastic variables of the network such as wind power generators (WPG) do not follow the forecasted production in real-time and have some distortions. Stochastic two-stage programming is applied to manage DR options, including load curtailment (LC), load shifting (LS), and load recovery (LR) in both day-ahead and real-time market. DR options in real-time are scheduled based on possible scenarios that reflect the behavior of wind power generation and are generated through Monte-Carlo simulation method. The merits of the method are demonstrated in a 6-bus case study, which shows a reduction in total operation cost.

Author(s):

Saber Talari    
UBI
Portugal

Miadreza Shafie-khah    
UBI
Portugal

Fei Wang    
North China Electric Power University
China

João Catalão    
FEUP and INESC TEC
Portugal

 

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