Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms
Original Research|更新时间:2026-09-30
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Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms
Protection and Control of Modern Power SystemsVol. 5, Issue 1, Pages: 1-15(2020)
作者机构:
Department of Electrical Engineering, National Institute of Technology, Warangal, Telengana,India
Satish Kumar Injeti, Vinod Kumar Thunuguntla. Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms[J]. Protection and Control of Modern Power Systems, 2020, 5(1): 1-15.
DOI:
Satish Kumar Injeti, Vinod Kumar Thunuguntla. Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms[J]. Protection and Control of Modern Power Systems, 2020, 5(1): 1-15.DOI: 10.1186/s41601-019-0149-x.
Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms
Purpose: The 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 (24 h) power loss and voltage improvement of the system as objectives for better system performance. Design/methodology/approach: To 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. Findings: The 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/value: The 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.
Abstract
Purpose: The 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 (24 h) power loss and voltage improvement of the system as objectives for better system performance. Design/methodology/approach: To 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. Findings: The 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/value: The 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.