An Online Adaptive Intelligent Framework for Customer Willingness Interpretation in Demand Response Exchange

The demand response exchange presents an independent pool based market clearing mechanism dedicated for resources in the demand side. The active demand resources participate in the pool acting as demand response buyers. The of such buyers can be better represented by utilizing the concepts of fuzzy systems. This paper presents a methodology to enhance the benefit of DR sellers and buyers in the demand response exchange through fuzzy inference system. However, the performance of the fuzzy system is dependent on the structure of membership function and rule base. Thus, an adaptive way of membership function tuning has been adopted in this paper. The tuning of the parameters has been performed using various heuristic approaches to observe the performance of tuned fuzzy system for DRX application compared to traditional non- fuzzy and un-tuned models. The simulation experiments carried out with different load types in different seasons demonstrate the improvement in DRX welfare for adaptively tuned fuzzy system to the traditional and un-tuned models. The adaptive tuning presented in this paper can be used by individual DR seller to calculate the participation bids.