Particle Swarm Based Optimization of Power Losses in Network Using STATCOM

Tuzikova, Valeriya; Müller, Zdeněk; Švec, Ján; Valouch, Viktor; Tlustý, Josef

doi:10.24084/repqj12.337

Cited by 1 publication

(1 citation statement)

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“…As for the components model, the losses are mainly caused due to line impedances. Therefore, the recommendation for the system is to be highly analyzed, monitored and minimized [8]. Mathematically, the objective function of the problem is described as:…”

Section: Objective Functionsmentioning

confidence: 99%

Multi-objective Optimization of Afghanistan Kabul City Distribution Network for Real-time Voltage Control and Power Loss Reduction

Noorzad¹,

Senjyu²

2017

ujes

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Afghanistan Kabul City Distribution System (KDS) is functioning in adverse condition, and there is always programmed or un-programmed load shedding imposed by the Power Distribution Company. There are four indicators to be optimized for the sustainability of KDS, power loss reduction, stability, reliability, preservation and protection. In this paper, the optimization of power loss reduction and optimal voltage control of Kabul Distribution System (KDS) in the presence of Distributed Generation (DG) and Step-Voltage Regulator (SVR) connected to the network is proposed. In particular, Kabul city has plentiful sources of renewable energy such as Photovoltaic (PV) and wind power as a countermeasure for diminishing the losses of the system. The Multi-Objective Particle Swarm Optimization (MOPSO) based on two objective functions regarding hourly power loss reduction and voltage profile improvement of the distribution network is considered. The application of PV as DG in distribution system regarding their optimal number, size, and location justifies as loss reduction, reducing the entire grid peak demand and minimizing the congestion of the network. However, the optimized tap ratios and position of SVR are treats to enhance and stabilize the voltage prole and to control the violation of the system voltage according to load conditions. The 24 hours technical data of the practically functioning Kabul city Distribution System Junction Station II are used as a case study. Finally, the proposed algorithm has been simulated using MATLAB R software, and the results are presented.

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Section: Objective Functionsmentioning

confidence: 99%