Title :
Economic dispatch for microgrid containing electric vehicles via probabilistic modelling
Author :
Yin Yao; Wenzhong Gao;James Momoh;Eduard Muljadi
Author_Institution :
Department of Electrical and Computer Engineering, University of Denver, CO 80210 USA
Abstract :
In this paper, an economic dispatch model with probabilistic modeling is developed for microgrid. Electric power supply in microgrid consists of conventional power plants and renewable energy power plants, such as wind and solar power plants. Due to the fluctuation of solar and wind plants´ output, an empirical probabilistic model is developed to predict their hourly output. According to different characteristics of wind and solar plants, the parameters for probabilistic distribution are further adjusted individually for both power plants. On the other hand, with the growing trend of Plug-in Electric Vehicle (PHEV), an integrated microgrid system must also consider the impact of PHEVs. Not only the charging loads from PHEVs, but also the discharging output via Vehicle to Grid (V2G) method can greatly affect the economic dispatch for all the micro energy sources in microgrid. This paper presents an optimization method for economic dispatch in microgrid considering conventional, renewable power plants, and PHEVs. The simulation results reveal that PHEVs with V2G capability can be an indispensable supplement in modern microgrid.
Keywords :
"Microgrids","Wind farms","Power generation","Economics","Cost function","Renewable energy sources","Wind forecasting"
Conference_Titel :
North American Power Symposium (NAPS), 2015
DOI :
10.1109/NAPS.2015.7335258