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

Bharath Varsh Rao, Friederich Kupzog and Martin Kozek
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Bharath Varsh Rao: Electric Energy Systems—Center for Energy, AIT Austrian Institute of Technology, 1210 Vienna, Austria
Friederich Kupzog: Electric Energy Systems—Center for Energy, AIT Austrian Institute of Technology, 1210 Vienna, Austria
Martin Kozek: Institute of Mechanics and Mechatronics—Faculty of Mechanical and Industrial Engineering, Vienna University of Technology, 1060 Vienna, Austria

Sustainability, 2019, vol. 11, issue 6, 1-16

Abstract: 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.

Keywords: unbalanced three-phase distribution networks; optimal power flows; genetic algorithm; holomorphic embedding load flow method; simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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