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Optimal Management of Reactive Power Considering Voltage and Location of Control Devices Using Artificial Bee Algorithm

doi: 10.3390/app12010027
Reactive power compensation is one of the practical tools that can be used to improve power systems and reduce costs. These benefits are achieved when the compensators are installed in a suitable place with optimal capacity. This study solves the issues of optimal supply and the purchase of reactive power in the IEEE 30-bus power system, especially when considering voltage stability and reducing total generation and operational costs, including generation costs, reserves, and the installation of reactive power control devices. The modified version of the artificial bee colony (MABC) algorithm is proposed to solve optimization problems and its results are compared with the artificial bee colony (ABC) algorithm, the particle swarm optimization (PSO) algorithm and the genetic algorithm (GA). The simulation results showed that the minimum losses in the power system requires further costs for reactive power compensation. Also, optimization results proved that the proposed MABC algorithm has a lower active power loss, reactive power costs, a better voltage profile and greater stability than the other three algorithms.
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- Anhui University of Science and Technology China (People's Republic of)
- Fukuoka Institute of Technology Japan
- Semnan University Iran (Islamic Republic of)
Technology, QH301-705.5, T, Physics, QC1-999, Engineering (General). Civil engineering (General), Chemistry, voltage stability, artificial bee colony algorithm, TA1-2040, Biology (General), control devices; artificial bee colony algorithm; voltage stability; reactive power, control devices, reactive power, QD1-999
Technology, QH301-705.5, T, Physics, QC1-999, Engineering (General). Civil engineering (General), Chemistry, voltage stability, artificial bee colony algorithm, TA1-2040, Biology (General), control devices; artificial bee colony algorithm; voltage stability; reactive power, control devices, reactive power, QD1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).36 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
