Economic Dispatch for Microgrid Containing Electric Vehicles via Probabilistic Modeling: Preprint

Eduard Muljadi, Yin Yao, Wenzhong Gao, James Momoh

Research output: Contribution to conferencePaper

Abstract

In this paper, an economic dispatch model with probabilistic modeling is developed for a microgrid. The electric power supply in a microgrid consists of conventional power plants and renewable energy power plants, such as wind and solar power plants. Because of the fluctuation in the output of solar and wind power plants, an empirical probabilistic model is developed to predict their hourly output. According to different characteristics of wind and solar power plants, the parameters for probabilistic distribution are further adjusted individually for both. On the other hand, with the growing trend in plug-in electric vehicles (PHEVs), an integrated microgrid system must also consider the impact of PHEVs. The charging loads from PHEVs as well as the discharging output via the vehicle-to-grid (V2G) method can greatly affect the economic dispatch for all of the micro energy sources in a microgrid. This paper presents an optimization method for economic dispatch in a microgrid considering conventional power plants, renewable power plants, and PHEVs. The simulation results reveal that PHEVs with V2G capability can be an indispensable supplement in a modern microgrid.
Original languageAmerican English
Number of pages8
StatePublished - 2016
EventNorth American Power Symposium - Charlotte, North Carolina
Duration: 4 Oct 20156 Oct 2015

Conference

ConferenceNorth American Power Symposium
CityCharlotte, North Carolina
Period4/10/156/10/15

NREL Publication Number

  • NREL/CP-5D00-64835

Keywords

  • economic dispatch
  • microgrid
  • plug-in hybrid electric vehicles (PHEV)
  • probabilistic distribution model
  • stochastic model
  • transportation electrification

Fingerprint

Dive into the research topics of 'Economic Dispatch for Microgrid Containing Electric Vehicles via Probabilistic Modeling: Preprint'. Together they form a unique fingerprint.

Cite this