Robust Operation of Soft Open Points in Active Distribution Networks With High Penetration of Photovoltaic Integration

Ji, Haoran; Wang, Chengshan; Li, Peng; Ding, Fei; Wu, Jianzhong

doi:10.1109/tste.2018.2833545

Cited by 171 publications

(97 citation statements)

References 33 publications

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“…where A SOP loss is the loss coefficient of VSCs, which represents leakage in the transferred power to the total power transferred between feeders [33,40,41].…”

Section: Sop Modelingmentioning

confidence: 99%

“…In order to validate the effectiveness of Scenario 9 proposed in this work, it was examined on an 83-node balanced distribution system from a power company in Taiwan, in which the 83-node base configuration consisted of 83 sectionalized lines and 13 tie-lines, as shown in Figure 7. The number of SOPs that can be installed ranges from 1 to 5, i.e., N SOP ∈ [1,5], where the individual SOP rating (S SOP I = S SOP J ) is 1.5 MVA and A SOP loss equals 0.02 [33,40,41]. N DG is set to 8 with S DG equal to 3 MVA and PF ranges from 0.95 lagging to unity.…”

Section: -Node Distribution Systemmentioning

confidence: 99%

“…Also, I rated b is set to 310 A. configuration consisted of 83 sectionalized lines and 13 tie-lines, as shown in Figure 7. The number of SOPs that can be installed ranges from 1 to 5, i.e., ∈ 1,5], where the individual SOP rating ( = ) is 1.5 MVA and equals 0.02 [33,40,41]. is set to 8 with equal to 3 MVA and PF ranges from 0.95 lagging to unity.…”

Section: -Node Distribution Systemmentioning

confidence: 99%

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Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

et al. 2019

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In this study, we allocated soft open points (SOPs) and distributed generation (DG) units simultaneously with and without network reconfiguration (NR), and investigate the contribution of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to distribution systems under different loading conditions. A recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of SOPs and DGs allocation, along with new NR methodology to obtain radial configurations in an efficient manner without the possibility of getting trapped in local minima. Further, multi-scenario studies are conducted on an IEEE 33-node balanced benchmark distribution system and an 83-node balanced distribution system from a power company in Taiwan. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. It was clear from the results obtained that simultaneous NR, SOP, and DG allocation into a distribution system creates a hybrid configuration that merges the benefits offered by radial distribution systems and mitigates drawbacks related to losses, power quality, and voltage violations, while offering a far more efficient and optimal network operation. Also, it was found that the contribution of the internal loss of SOPs to the total loss for different numbers of installed SOPs is not dependent on the number of SOPs and that loss minimization is not always guaranteed by installing more SOPs or DGs along with NR. One of the findings of the paper demonstrates that NR with optimizing tie-lines could reduce active losses considerably. The results obtained also validate, with proper justifications, that SOPs installed for the management of constraints in LV feeders could further reduce losses and efficiently address issues related to voltage violations and network losses.

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“…where A SOP loss is the loss coefficient of VSCs, which represents leakage in the transferred power to the total power transferred between feeders [33,40,41].…”

Section: Sop Modelingmentioning

confidence: 99%

Section: -Node Distribution Systemmentioning

confidence: 99%

Section: -Node Distribution Systemmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

et al. 2019

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show abstract

“…The number of SOPs that can be installed ranges from 1 to 5, i.e. ∈ [1,5], where the individual SOP rating ( = ) is 1 MVA and equals 0.02 [32], [41], [42]. is set to 3 while equals 1 MVA with unity PF.…”

Section: Ieee 33-node Distribution Systemmentioning

confidence: 99%

Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Diaaeldin¹,

Aleem²,

El-Rafei³

et al. 2019

Preprint

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In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.

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“…[2,3], while bringing new challenges to the planning and operation of distribution system like voltage violation [4], bi-direction power flow [5], power flow fluctuations [6]. In recent years, distributed energy storage (DES) as an important measure to alleviate the above problems has developed rapidly in both economic and technical aspects [7,8]. Compared with large-scale centralized energy storage plants, DES has fewer restrictions on the geographical conditions of installation location and performs an increasingly important part in various application scenarios of ADNs [9].…”

Section: Introductionmentioning

confidence: 99%

Parameterized Modeling and Planning of Distributed Energy Storage in Active Distribution Networks

Zhao

Song

et al. 2019

Applied Sciences

Self Cite

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In recent years, distributed energy storage (DES) has experienced rapid growth and has been widely applied in active distribution networks (ADNs). Owing to the close correlation between the characteristics and the application scenarios, DES modeling needs to be parameterized separately for various application demands. In this paper, a parameterized model for optimal DES planning in ADNs is proposed. The typical scenarios for DES planning are generated by the clustering technique, containing the patterns of load demand, wind turbine output and photovoltaic output. Secondly, an optimal planning model of DES considering parameterized characteristics is established, which is essentially a mixed integer non-linear optimization problem. Then, the model is converted to a mixed-integer second-order cone programming model, which can be solved efficiently by available commercial software. Finally, case studies on the modified IEEE 33-node system and IEEE 123-node system verify the efficiency of the proposed method, and the effects of DES planning are validated by two evaluation indexes.

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Robust Operation of Soft Open Points in Active Distribution Networks With High Penetration of Photovoltaic Integration

Cited by 171 publications

References 33 publications

Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Optimal Network Reconfiguration in Active Distribution Networks with Soft Open Points and Distributed Generation

Parameterized Modeling and Planning of Distributed Energy Storage in Active Distribution Networks

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