Paper Info
Title
Frequency control using on-line learning method for island smart grid with EVs and PVs
Abstract
Due to the intermittent power generation from renewable energy in the smart grid (i.e., photovoltaic (PV) or wind farm), large frequency fluctuation occurs when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. This problem may become worsen when the system is in island operating. Meanwhile, in the near future, electric vehicles (EVs) will be widely used by customers, where the EV station could be treated as dispersed battery energy storage. Therefore, the vehicle-to-grid (V2G) power control can be applied to compensate for inadequate LFC capacity, thus improving the island smart grid frequency stability. In this paper, an on-line learning method, called goal representation adaptive dynamic programming (GrADP), is adopted to coordinate control of units in an island smart grid. In the controller design, adaptive supplementary control signals are provided to proportional-integral (PI) controllers by online GrADP according to the utility function. Simulations on a benchmark smart grid with micro turbine (MT), EVs and PVs demonstrate the superior control effect and robustness of the proposed coordinate controller over the original PI controller and fuzzy controller.
Year
DOI
Venue
2014
10.1109/IJCNN.2014.6889829
IJCNN
Keywords
Field
DocType
photovoltaic power systems,frequency stability,pi control,island operating,large frequency fluctuation,power control,proportional-integral controllers,photovoltaic,lfc capacity,electric power generation,load-frequency control capacity,on-line learning method,renewable energy,goal representation adaptive dynamic programming,online gradp,renewable energy sources,intermittent power generation,pi controllers,micro turbine,wind farm,adaptive control,ev station,controller design,adaptive supplementary control signals,smart power grids,benchmark smart grid,island smart grid frequency stability,dynamic programming,vehicle-to-grid power control,fuzzy controller,electric vehicles,benchmark testing,oscillators,smart grids,mathematical model,fuzzy logic,frequency control
Control theory,Smart grid,PID controller,Control theory,Computer science,Power control,Automatic frequency control,Robustness (computer science),Photovoltaic system,Electricity generation
Conference
ISSN
Citations 
PageRank 
2161-4393
4
0.52
References 
Authors
10
5
Name
Order
Citations
PageRank
Yufei Tang120322.83
Jun Yang282.27
Jun Yan317913.72
Zhili Zeng440.52
Haibo He53653213.96