Abstract (EN):
Due to the recent developments in smart grid area, demand response (DR) based load pattern evaluations have gained more attention in the literature. The elasticity of load pattern related to the consumer preferences, the ratio of employing DR activities and the types of controllable loads affecting load pattern are prior topics to be evaluated in terms of better and more effective market regulation, especially in day-ahead and real time periods. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) based method combined with a General Algebraic Modeling System (GAMS)-based training pattern creation is presented in order to assess the effect of demand elasticity driven by DR activities in a day-ahead pool.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
5