Multi-objective time-variant optimum automatic and fixed type of capacitor bank allocation considering minimization of switching steps

Mikaeel Ahmadi; Mir Sayed Shah Danish; Mohammed Elsayed Lotfy; Atsushi Yona; Ying-Yi Hong; Tomonobu Senjyu; Mikaeel Ahmadi; Mir Sayed Shah Danish; Mohammed Elsayed Lotfy; Atsushi Yona; Ying-Yi Hong; Tomonobu Senjyu

doi:10.3934/energy.2019.6.792

AIMS Energy

2019, Volume 7, Issue 6: 792-818. doi: 10.3934/energy.2019.6.792

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Multi-objective time-variant optimum automatic and fixed type of capacitor bank allocation considering minimization of switching steps

1.
Faculty of Engineering, University of the Ryukyus, Nishihara-city, Okinawa 903-0213, Japan
2.
Department of Electrical Engineering Chung Yuan Christian University Taoyuan 32023, Taiwan

Received: 29 August 2019 Accepted: 29 October 2019 Published: 20 November 2019

In this study, optimal methodologies including multi-objective optimization are proposed for allocation of automatic and fixed capacitors in the real distribution system on a daily basis. Minimizing the cost of energy loss and switching operation of the capacitors as the significant factors are considered correspondingly. Capacitors as a reactive power compensator have been recognized in the power system for a long time before. Their impact on voltage improvement as well as the loss of energy reduction significantly has been investigated to not only enhance the network’s power quality but provides profit by cost savings for utility managers. Such an approach could be obtainable via their optimum consideration in power system planning and operation. In this research, two methodologies are proposed for placement and sizing of both automatic and fixed types of capacitors. The first methodology exploits two steps mechanism for capacitor allocation in which, optimum locations and sizes are identified via inexpensive sensitivity analysis and epsilon multi-objective genetic algorithm (∊-MOGA), respectively. However, successful application results are obtained, the second methodology utilizing only ∊-MOGA for both sizing and placement is compared to the first methodology to prioritize each method. The simulations are performed in MATLAB^® through its efficient application on the complex real 162-bus distribution network. The detailed discussions and conclusion based on the obtained results are extended in this paper accordingly.
- distribution network,
- energy loss,
- automatic capacitor bank,
- Multi-objective optimization,
- sensitivity analysis,
- ∊-MOGA
Citation: Mikaeel Ahmadi, Mir Sayed Shah Danish, Mohammed Elsayed Lotfy, Atsushi Yona, Ying-Yi Hong, Tomonobu Senjyu. Multi-objective time-variant optimum automatic and fixed type of capacitor bank allocation considering minimization of switching steps[J]. AIMS Energy, 2019, 7(6): 792-818. doi: 10.3934/energy.2019.6.792

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Abstract

In this study, optimal methodologies including multi-objective optimization are proposed for allocation of automatic and fixed capacitors in the real distribution system on a daily basis. Minimizing the cost of energy loss and switching operation of the capacitors as the significant factors are considered correspondingly. Capacitors as a reactive power compensator have been recognized in the power system for a long time before. Their impact on voltage improvement as well as the loss of energy reduction significantly has been investigated to not only enhance the network’s power quality but provides profit by cost savings for utility managers. Such an approach could be obtainable via their optimum consideration in power system planning and operation. In this research, two methodologies are proposed for placement and sizing of both automatic and fixed types of capacitors. The first methodology exploits two steps mechanism for capacitor allocation in which, optimum locations and sizes are identified via inexpensive sensitivity analysis and epsilon multi-objective genetic algorithm (∊-MOGA), respectively. However, successful application results are obtained, the second methodology utilizing only ∊-MOGA for both sizing and placement is compared to the first methodology to prioritize each method. The simulations are performed in MATLAB^® through its efficient application on the complex real 162-bus distribution network. The detailed discussions and conclusion based on the obtained results are extended in this paper accordingly.

References

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