Adjustable Robust Optimal Power Flow Considering Random Output of Various Renewable Energy Integration in Complex Three-phase Distribution Networks

2019 ◽  
Author(s):  
Yiqi Cao ◽  
Junwei Liu ◽  
Danping Wang
Keyword(s):  
Renewable Energy ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Phase Distribution ◽  
Distribution Networks ◽  
Energy Integration ◽  
Renewable Energy Integration ◽  
Optimal Power ◽  
Three Phase

scholarly journals Three-Phase Unbalanced Optimal Power Flow Using Holomorphic Embedding Load Flow Method

2019 ◽  
Vol 11 (6) ◽  
pp. 1774 ◽  
Author(s):  
Bharath Rao ◽  
Friederich Kupzog ◽  
Martin Kozek
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Distribution Networks ◽  
Optimization Method ◽  
Load Flow ◽  
Flow Method ◽  
Optimal Power ◽  
Three Phase ◽  
Holomorphic Embedding

Distribution networks are typically unbalanced due to loads being unevenly distributed over the three phases and untransposed lines. Additionally, unbalance is further increased with high penetration of single-phased distributed generators. Load and optimal power flows, when applied to distribution networks, use models developed for transmission grids with limited modification. The performance of optimal power flow depends on external factors such as ambient temperature and irradiation, since they have strong influence on loads and distributed energy resources such as photo voltaic systems. To help mitigate the issues mentioned above, the authors present a novel class of optimal power flow algorithm which is applied to low-voltage distribution networks. It involves the use of a novel three-phase unbalanced holomorphic embedding load flow method in conjunction with a non-convex optimization method to obtain the optimal set-points based on a suitable objective function. This novel three-phase load flow method is benchmarked against the well-known power factory Newton-Raphson algorithm for various test networks. Mann-Whitney U test is performed for the voltage magnitude data generated by both methods and null hypothesis is accepted. A use case involving a real network in Austria and a method to generate optimal schedules for various controllable buses is provided.

scholarly journals Research on three-phase optimal power flow for distribution networks based on constant Hessian matrix

2018 ◽  
Vol 12 (1) ◽  
pp. 241-246 ◽  
Author(s):  
Fengzhan Zhao ◽  
Tingting Zhao ◽  
Yuntao Ju ◽  
Kang Ma ◽  
Xianfei Zhou
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Hessian Matrix ◽  
Distribution Networks ◽  
Optimal Power ◽  
Three Phase

Mapping Flexibility Region through Three-phase Distribution Optimal Power Flow at TSO-DSO Point of Interconnection

2021 ◽  
Author(s):  
Sergio Bruno ◽  
Giovanni Giannoccaro ◽  
Cosimo Iurlaro ◽  
Massimo La Scala ◽  
Luca Notaristefano ◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Phase Distribution ◽  
Optimal Power ◽  
Three Phase

scholarly journals An Optimal Power Flow Algorithm for the Simulation of Energy Storage Systems in Unbalanced Three-Phase Distribution Grids

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1623
Author(s):  
Lukas Held ◽  
Felicitas Mueller ◽  
Sina Steinle ◽  
Mohammed Barakat ◽  
Michael R. Suriyah ◽  
...  
Keyword(s):  
Energy Storage ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Phase Distribution ◽  
Storage Systems ◽  
Optimal Power ◽  
Three Phase ◽  
Flow Algorithm ◽  
Distribution Grids

An optimal power flow algorithm for unbalanced three-phase distribution grids is presented in this paper as a new tool for grid planning on low voltage level. As additional equipment like electric vehicles, heat pumps or solar power systems can sometimes cause unbalanced power flows, existing algorithms have to be adapted. In comparison to algorithms considering balanced power flows, the presented algorithm uses a complete model of a three-phase four-wire low voltage grid. Additionally, a constraint for the voltage unbalance in the grid is introduced. The algorithm can be used to optimize the operation of energy storage systems in unbalanced systems. The used grid model, constraints, objective function and solver are explained in detail. A validation of the algorithm using a commercial tool is done. Additionally, three exemplary optimizations are performed to show possible applications for this tool.

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