Multi-objective optimal operation of micro-grid with plug-in electric vehicles

Author

Hao Xiao ; Wei Pei ; Yanhong Yang ; Hui Qu ; Zhiping Qi ; Li Kong

Author_Institution

Inst. of Electr. Eng., Beijing, China

fYear

2014

fDate

Aug. 31 2014-Sept. 3 2014

Firstpage

1

Lastpage

5

Abstract

A multi-objective operational scheduling model with plug-in electric vehicles (PEVs) is proposed to minimize the operation cost and to improve the load characteristic of Micro-grid. In this model, the PEVs charging power and the distribute generations (DGs) output power of each time period are selected as decision variables, the driving behavior of PEVs is also taken into account. Multi-objective evolution algorithm NSGA-II is utilized to solve the multi-objective model and fuzzy clustering method is introduced to help obtaining the best Pareto front. The presented model is tested on the IEEE 34-node test feeder, the results obtained demonstrate the effectiveness of the proposed dispatching approach.

Keywords

Pareto optimisation; battery powered vehicles; distributed power generation; load dispatching; pattern clustering; power distribution economics; power generation economics; secondary cells; IEEE 34-node test feeder; NSGA-II; PEV; Pareto front; charging power; driving behavior; fuzzy clustering method; load dispatching; microgrid optimal operation; multiobjective evolution algorithm; multiobjective model; multiobjective optimal operation; operation cost minimization; plug-in electric vehicles; Batteries; Electric vehicles; Electricity; Load modeling; Mathematical model; Optimization; Probability distribution; Micro-grid; NSGA-II; fuzzy clustering; multi-objective; optimal operation; plug-in electric vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo

Conference_Location

Beijing

Print_ISBN

978-1-4799-4240-4

Type

conf

DOI

10.1109/ITEC-AP.2014.6941105

Filename

6941105