Paper Info
Title
Intelligent load frequency controller using GrADP for island smart grid with electric vehicles and renewable resources
Abstract
Increasing deployment of intermittent power generation from renewable resources in the smart grid, such as photovoltaic (PV) or wind farm, will cause large system frequency fluctuation when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. Even worse, the system inertia will decrease when the smart grid is in island operating mode, which would degrade system damping and cause system instability. Meanwhile, electric vehicles (EVs) will be widely used by customers in the near future, where the EV station could be treated as dispersed battery energy storage. Therefore, the vehicle-to-grid (V2G) technology can be employed to compensate for inadequate LFC capacity, thus improving the island smart grid frequency stability. In this paper, an on-line reinforcement learning (RL) based method, called goal representation adaptive dynamic programming (GrADP), is employed to adaptive control of units in an island smart grid. In the controller design, adaptive supplementary control signals are provided to proportional-integral-derivative (PID) controller by GrADP in a real-time manner. Comparative simulation studies on a benchmark smart grid with micro-turbine (MT), EVs, PV array and wind power are carried out among the GrADP controller, the original PID controller and the particle swarm optimization (PSO) based fuzzy logic controller. Simulation results demonstrate competitive performance and satisfied learning ability of the GrADP based coordinate controller. Moreover, the impact of signal transmission delay on the control performance is also considered, and suggestions to address this issue are given in the paper.
Year
DOI
Venue
2015
10.1016/j.neucom.2015.04.092
Neurocomputing
Keywords
Field
DocType
Load-frequency control (LFC),Goal representation adaptive dynamic programming (GrADP),Fuzzy logic,Electric vehicle (EV),Signal transmission delay
Automotive engineering,Control theory,Artificial intelligence,Photovoltaic system,Wind power,Particle swarm optimization,Control theory,Smart grid,PID controller,Adaptive control,Machine learning,Electricity generation,Mathematics
Journal
Volume
Issue
ISSN
170
C
0925-2312
Citations 
PageRank 
References 
7
0.56
20
Authors
4
Name
Order
Citations
PageRank
Yufei Tang120322.83
Jun Yang2171.04
Jun Yan317913.72
Haibo He43653213.96