Abstract

Renewable Energy Sources (RESs) are increasingly integrated into distribution networks due to their undeniable technical and environmental advantages. Despite all the economical and environmental benefits of RESs, they can negatively affect the distribution network. For instance, their output generations are not predictable, and these uncertainties will lead to some operational challenges. Also, RESs are affected by the climate situation, and there are high correlations between them, generally. The correlations between RESs intensify the operational challenges of energy systems. Soft open points (SOPs) are flexible power electronic devices that can effectively increase the efficiency of energy systems. They realize accurate active power control and reactive power compensation to reduce power losses and adjust three-phase voltages. This paper focused on the optimal determination of the location and setting points of SOPs in unbalanced distribution networks in the presence of correlated uncertain sources. The genetic algorithm (GA) was used to solve the main optimization problem, and the correlation between uncertain sources was managed by the Nataf transformation technique. The IEEE 37 bus test system was utilized to illustrate the effectiveness of the proposed method.

Highlights

  • Reference [6] has investigated the effect of the number of Soft open points (SOPs) installed in the distribution network on ameliorating the voltage profile as well as, reducing active power losses and load balancing by using the genetic algorithm (GA) and improved

  • By installing an SOP between buses 2 and 28 and setting the set-points according to Table 2, the power losses are reduced from 32.64 kW to 24.8 and the voltage unbalance index (VUI) is reduced from 20.98% to 9.57 %

  • In this paper, the SOP is used to improve the performance of the unbalanced distribution networks

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Summary

INTRODUCTION

SOP are power electronic devices installed in normally open points that can provide effective control of active and reactive power flow among feeders [5] In this way, the application of fast probabilistic assessment methods with a high level of accuracy is considered for correlation management [4]. Reference [6] has investigated the effect of the number of SOPs installed in the distribution network on ameliorating the voltage profile as well as, reducing active power losses and load balancing by using the GA and improved. In reference [7], the optimal use of energy storage devices in the presence of SOP, distributed generation sources, and network reconfiguration have been investigated to reduce the cost of network utilization, decrease losses, and improve the voltage profile.

WIND GENERATION
SOP MODELLING
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