The multi-voltage-level DC distribution network(MVL-DC-DN)is a promising network for efficiently integrat ing rapidly growing DC loads,and fast-growing load demand would bring a challenge to the MVL-DC-DN in terms of ...The multi-voltage-level DC distribution network(MVL-DC-DN)is a promising network for efficiently integrat ing rapidly growing DC loads,and fast-growing load demand would bring a challenge to the MVL-DC-DN in terms of the maximum loadability.This paper considers the DC electric spring(DC-ES)as a novel candidate flexible resource for en hancing the maximum loadability of the MVL-DC-DN,and pro poses an evaluation method for the maximum loadability.First ly,with the consideration of device constraints,the impact that the DC-ES on the maximum loadability of the DC distribution network(DC-DN)is analyzed via a simplified equivalent cir cuit.Subsequently,the power flow(PF)model of an MVL-DCDN with DC-ESs is established.Finally,a method based on con tinuation power flow(CPF)for evaluating the maximum load ability of an MVL-DC-DN with DC-ESs is proposed.During the evaluation,limitations of the DC-ES and the DC transform er(DCT)are considered.The consideration of the practical con straints avoids the overestimation of the maximum loadability.The case study verifies the effectiveness of the proposed method.展开更多
In a Power System, load is the most uncertain and extremely time varying unit. Hence it is important to determine the system’s supreme acceptable loadability limit called maximum loadability point to accommodate...In a Power System, load is the most uncertain and extremely time varying unit. Hence it is important to determine the system’s supreme acceptable loadability limit called maximum loadability point to accommodate the sudden variation of load demand. Nowadays the enhancement of the maximum loadability point is essential to meet the rapid growth of load demand by improvising the system’s load utilization capacity. Flexible AC Transmission system devices (FACTS) with their speed and flexibility will play a key role in enhancing the controllability and power transfer capability of the system. Considering the theme of FACTS devices in the loadability limit enhancement, in this paper maximum loadability limit determination and its enhancement are prepared with the help of swarm intelligence based meta-heuristic Firefly Algorithm(FFA) by finding the optimal loading factor for each load and optimally placing the SVC (Shunt Compensation) and TCSC (Series Compensation) FACTS devices in the system. To illuminate the effectiveness of FACTS devices in the loadability enhancement, the line contingency scenario is also concerned in the study. The study of FACTS based maximum system load utilization acceptability point determination is demonstrated with the help of modified IEEE 30 bus, IEEE 57 Bus and IEEE 118 Bus test systems. The results of FACTS devices involvement in determining the maximum loading point enhance the load utilization point in normal state and also help to overcome the system violation in transmissionline contingency state. Also the firefly algorithm in determining the maximum loadability point provides better search capability with faster convergence rate compared to that of Particle swarm optimization (PSO) and Differential evolution algorithm.展开更多
基金supported in part by the National Natural Science Foundation of China(No.52077017).
文摘The multi-voltage-level DC distribution network(MVL-DC-DN)is a promising network for efficiently integrat ing rapidly growing DC loads,and fast-growing load demand would bring a challenge to the MVL-DC-DN in terms of the maximum loadability.This paper considers the DC electric spring(DC-ES)as a novel candidate flexible resource for en hancing the maximum loadability of the MVL-DC-DN,and pro poses an evaluation method for the maximum loadability.First ly,with the consideration of device constraints,the impact that the DC-ES on the maximum loadability of the DC distribution network(DC-DN)is analyzed via a simplified equivalent cir cuit.Subsequently,the power flow(PF)model of an MVL-DCDN with DC-ESs is established.Finally,a method based on con tinuation power flow(CPF)for evaluating the maximum load ability of an MVL-DC-DN with DC-ESs is proposed.During the evaluation,limitations of the DC-ES and the DC transform er(DCT)are considered.The consideration of the practical con straints avoids the overestimation of the maximum loadability.The case study verifies the effectiveness of the proposed method.
文摘In a Power System, load is the most uncertain and extremely time varying unit. Hence it is important to determine the system’s supreme acceptable loadability limit called maximum loadability point to accommodate the sudden variation of load demand. Nowadays the enhancement of the maximum loadability point is essential to meet the rapid growth of load demand by improvising the system’s load utilization capacity. Flexible AC Transmission system devices (FACTS) with their speed and flexibility will play a key role in enhancing the controllability and power transfer capability of the system. Considering the theme of FACTS devices in the loadability limit enhancement, in this paper maximum loadability limit determination and its enhancement are prepared with the help of swarm intelligence based meta-heuristic Firefly Algorithm(FFA) by finding the optimal loading factor for each load and optimally placing the SVC (Shunt Compensation) and TCSC (Series Compensation) FACTS devices in the system. To illuminate the effectiveness of FACTS devices in the loadability enhancement, the line contingency scenario is also concerned in the study. The study of FACTS based maximum system load utilization acceptability point determination is demonstrated with the help of modified IEEE 30 bus, IEEE 57 Bus and IEEE 118 Bus test systems. The results of FACTS devices involvement in determining the maximum loading point enhance the load utilization point in normal state and also help to overcome the system violation in transmissionline contingency state. Also the firefly algorithm in determining the maximum loadability point provides better search capability with faster convergence rate compared to that of Particle swarm optimization (PSO) and Differential evolution algorithm.
