This study proposes a graphical user interface(GUI) based on an enhanced bacterial foraging optimization(EBFO) to find the optimal locations and sizing parameters of multi-type DFACTS in large-scale distribution syste...This study proposes a graphical user interface(GUI) based on an enhanced bacterial foraging optimization(EBFO) to find the optimal locations and sizing parameters of multi-type DFACTS in large-scale distribution systems.The proposed GUI based toolbox,allows the user to choose between single and multiple DFACTS allocations,followed by the type and number of them to be allocated.The EBFO is then applied to obtain optimal locations and ratings of the single and multiple DFACTS.This is found to be faster and provides more accurate results compared to the usual PSO and BFO.Results obtained with MATLAB/Simulink simulations are compared with PSO,BFO and enhanced BFO.It reveals that enhanced BFO shows quick convergence to reach the desired solution there by yielding superior solution quality.Simulation results concluded that the EBFO based multiple DFACTS allocation using DSSSC,APC and DSTATCOM is preferable to reduce power losses,improve load balancing and enhance voltage deviation index to 70%,38% and 132% respectively and also it can improve loading factor without additional power loss.展开更多
This paper demonstrates the controlling abilities of a large PV-farm as a Solar-PV inverter for mitigating the chaotic electrical,electromechanical,and torsional oscillations including Subsynchronous resonance in a tu...This paper demonstrates the controlling abilities of a large PV-farm as a Solar-PV inverter for mitigating the chaotic electrical,electromechanical,and torsional oscillations including Subsynchronous resonance in a turbogenerator-based power system.The oscillations include deviations in the machine speed,rotor angle,voltage fluctuations(lead-ing to voltage collapse),and torsional modes.During the night with no solar power generation,the PV-plant switches to PV-STATCOM mode and works as a Solar-PV inverter at its full capacity to attenuate the oscillations.During full sun in the daytime,on any fault detection,the PV-plant responds instantly and stops generating power to work as a Solar-PV inverter.The PV-farm operates in the same mode until the oscillations are fully alleviated.This paper mani-fests the control of the DC-link capacitor voltage of the Solar-PV inverter with a bacterial foraging optimization-based intelligent maximum power point tracking controller for the optimal control of active and reactive power.Kundur’s multi-machine model aggregated with PV-plant is modeled in the Matlab/Simulink environment to examine the rotor swing deviations with associated shaft segments.The results for different test cases of interest demonstrate the posi-tive outcomes of deploying large PV-farms as a smart PV-STATCOM for controlling power system oscillations.展开更多
基金Project supported by Borujerd Branch,Islamic Azad University,Iran
文摘This study proposes a graphical user interface(GUI) based on an enhanced bacterial foraging optimization(EBFO) to find the optimal locations and sizing parameters of multi-type DFACTS in large-scale distribution systems.The proposed GUI based toolbox,allows the user to choose between single and multiple DFACTS allocations,followed by the type and number of them to be allocated.The EBFO is then applied to obtain optimal locations and ratings of the single and multiple DFACTS.This is found to be faster and provides more accurate results compared to the usual PSO and BFO.Results obtained with MATLAB/Simulink simulations are compared with PSO,BFO and enhanced BFO.It reveals that enhanced BFO shows quick convergence to reach the desired solution there by yielding superior solution quality.Simulation results concluded that the EBFO based multiple DFACTS allocation using DSSSC,APC and DSTATCOM is preferable to reduce power losses,improve load balancing and enhance voltage deviation index to 70%,38% and 132% respectively and also it can improve loading factor without additional power loss.
文摘This paper demonstrates the controlling abilities of a large PV-farm as a Solar-PV inverter for mitigating the chaotic electrical,electromechanical,and torsional oscillations including Subsynchronous resonance in a turbogenerator-based power system.The oscillations include deviations in the machine speed,rotor angle,voltage fluctuations(lead-ing to voltage collapse),and torsional modes.During the night with no solar power generation,the PV-plant switches to PV-STATCOM mode and works as a Solar-PV inverter at its full capacity to attenuate the oscillations.During full sun in the daytime,on any fault detection,the PV-plant responds instantly and stops generating power to work as a Solar-PV inverter.The PV-farm operates in the same mode until the oscillations are fully alleviated.This paper mani-fests the control of the DC-link capacitor voltage of the Solar-PV inverter with a bacterial foraging optimization-based intelligent maximum power point tracking controller for the optimal control of active and reactive power.Kundur’s multi-machine model aggregated with PV-plant is modeled in the Matlab/Simulink environment to examine the rotor swing deviations with associated shaft segments.The results for different test cases of interest demonstrate the posi-tive outcomes of deploying large PV-farms as a smart PV-STATCOM for controlling power system oscillations.
