Optimal distribution reconfiguration considering high penetration of electric vehicles

Real power loss minimisation of smart grid with electric vehicles using distribution feeder reconfiguration

“…In [11], a genetic algorithm (GA) is employed to solve the DFR problem in the presence of an EV fleet. Similarly, the authors in [4,14] validated the ability of symbiotic organism search and social spider algorithm, respectively, to solve complex combinatorial DRF problem. Grey wolf optimisation (GWO) is a recent swarm intelligence (SI)-based technique which mimics the hunting behaviour of grey wolves.…”

“…The work presented in [13] showed that DFR with coordinated EV charging and discharging improves the operational cost of the system. In [14], the researchers studied DFR strategy for optimal operation and management of EV fleet considering V2G operation. Battery degradation cost due to discharging of EV fleet is not considered in [12][13][14].…”

“…In [14], the researchers studied DFR strategy for optimal operation and management of EV fleet considering V2G operation. Battery degradation cost due to discharging of EV fleet is not considered in [12][13][14]. The study in [4] aims to minimise the total operating cost of the system, considering distribution system automation under a stochastic framework with EV battery aging costs.…”

“…Similarly, the constructive influence of DFR with high penetration of wind power and V2G capability of the EV fleet is explored in [15] to minimise operation and reliability cost. In most of the works [4,[12][13][14][15] individual EVs are grouped under different fleets and each EV fleet is taken as an aggregated energy resource which neglects the constraints such as initial SOC, battery capacity and so on associated with individual EV.…”

“…The studies discussed above lay a groundwork to demonstrate that DFR has a high potential for line loss reduction, congestion management and reliability enhancement with high penetration of EVs load. The works presented in [4,[12][13][14][15] studied simultaneous scheduling of EV fleet and reconfiguration, while the work in [8][9][10] carried out DFR with EV demand profile obtained from uncoordinated, delayed and smart charging strategy. To the best of the authors' knowledge, the capability of DFR to improve the operation of the distribution system in the presence of EVs demand obtained under different scheduling strategies has not been well reported and compared in literature.…”