TY - JOUR
T1 - Automatic Generation Control Incorporating Electric Vehicles
AU - Oshnoei, Arman
AU - Khezri, Rahmat
AU - Muyeen, S.M.
AU - Oshnoei, Soroush
AU - Blaabjerg, Frede
PY - 2019/6
Y1 - 2019/6
N2 - Electrical vehicles (EVs) enjoying the new technology known as vehicle-to-grid have presented new opportunities to control and planning of power grids. Bidirectional connection capability of converters in EVs’ structure makes them a secure backup for frequency support. This paper applies EVs as one of the foremost controllable loads along with other conventional generation units for frequency control after disturbances in a multi-area power system. Application of tilt-integral-derivative (TID) controller for EVs has been addressed for the first time in this paper. In this regard, artificial bee colony optimization algorithm is employed for optimal tuning parameters of TID controllers in EV and automatic generation control structures. In order to achieve accurate and realistic results, physical limitations of generation rate constraint, non-linearity, and governor dead-band effect are included in the analysis. Eventually, three scenarios including step and random load changes, and sensitivity analysis are selected to illustrate the efficiency of the proposed coordinated control in terms of settling time, peak time, peak overshoot, and the integral of time multiplied squared error performance index in frequency and tie-line power deviations. The results are compared with particle swarm optimization and genetic algorithm based TID controllers.
AB - Electrical vehicles (EVs) enjoying the new technology known as vehicle-to-grid have presented new opportunities to control and planning of power grids. Bidirectional connection capability of converters in EVs’ structure makes them a secure backup for frequency support. This paper applies EVs as one of the foremost controllable loads along with other conventional generation units for frequency control after disturbances in a multi-area power system. Application of tilt-integral-derivative (TID) controller for EVs has been addressed for the first time in this paper. In this regard, artificial bee colony optimization algorithm is employed for optimal tuning parameters of TID controllers in EV and automatic generation control structures. In order to achieve accurate and realistic results, physical limitations of generation rate constraint, non-linearity, and governor dead-band effect are included in the analysis. Eventually, three scenarios including step and random load changes, and sensitivity analysis are selected to illustrate the efficiency of the proposed coordinated control in terms of settling time, peak time, peak overshoot, and the integral of time multiplied squared error performance index in frequency and tie-line power deviations. The results are compared with particle swarm optimization and genetic algorithm based TID controllers.
KW - Electrical vehicle
KW - Frequency control
KW - Artificial bee colony optimization
KW - Multi-area power system
KW - Tilt-integral-derivative controller
U2 - 10.1080/15325008.2019.1579270
DO - 10.1080/15325008.2019.1579270
M3 - Journal article
SN - 1532-5008
VL - 47
SP - 720
EP - 732
JO - Electric Power Components & Systems
JF - Electric Power Components & Systems
IS - 8
ER -