Optimal integration of DGs into radial distribution network in the presence of plug-in electric vehicles to minimize daily active power losses and to improve the voltage profile of the system using bio-inspired optimization algorithms

被引:91
作者
Injeti, Satish Kumar [1 ]
Thunuguntla, Vinod Kumar [1 ]
机构
[1] Natl Inst Technol Warangal, Dept Elect Engn, Warangal 506004, Telengana, India
关键词
Plug-in electric vehicles (PEVs); Distributed generators (DGs); Repetitive distribution power flow; Particle swarm optimization algorithm (PSO); Butterfly optimization (BO); Daily active power loss; LEARNING BASED OPTIMIZATION; OPTIMAL ALLOCATION; GENERATION ALLOCATION; OPTIMAL PLACEMENT; UNITS; RECONFIGURATION; STABILITY; LOCATION; SIZE;
D O I
10.1186/s41601-019-0149-x
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
PurposeThe increase in plug-in electric vehicles (PEVs) is likely to see a noteworthy impact on the distribution system due to high electric power consumption during charging and uncertainty in charging behavior. To address this problem, the present work mainly focuses on optimal integration of distributed generators (DG) into radial distribution systems in the presence of PEV loads with their charging behavior under daily load pattern including load models by considering the daily (24h) power loss and voltage improvement of the system as objectives for better system performance.Design/methodology/approachTo achieve the desired outcomes, an efficient weighted factor multi-objective function is modeled. Particle Swarm Optimization (PSO) and Butterfly Optimization (BO) algorithms are selected and implemented to minimize the objectives of the system. A repetitive backward-forward sweep-based load flow has been introduced to calculate the daily power loss and bus voltages of the radial distribution system. The simulations are carried out using MATLAB software.FindingsThe simulation outcomes reveal that the proposed approach definitely improved the system performance in all aspects. Among PSO and BO, BO is comparatively successful in achieving the desired objectives.Originality/valueThe main contribution of this paper is the formulation of the multi-objective function that can address daily active power loss and voltage deviation under 24-h load pattern including grouping of residential, industrial and commercial loads. Introduction of repetitive backward-forward sweep-based load flow and the modeling of PEV load with two different charging scenarios.
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页数:15
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