Comparison of AC Optimal Power Flow Methods in Low-Voltage Distribution Networks

The use of photovoltaic reactive power and energy storage active power can solve the problems of voltage violation, network loss, and three-phase unbalance caused by photovoltaic connection to low-voltage distribution networks. However, the three-phase four-wire structure of the low-voltage distribution network brings difficulties to power flow calculation. In order to achieve photovoltaic utilization through optimal power flow, a photovoltaic-energy storage collaborative control method for low-voltage distribution networks based on the optimal power flow of a three-phase four-wire system is proposed. Considering the amplitude and phase angle of voltage and current, a three-phase four-wire node admittance matrix was used to establish the network topology of the low-voltage distribution network. Also, to minimize the network loss, the three-phase unbalance and voltage deviation. a multi-objective optimization model based on three-phase four-wire network topology was established considering the voltage constraints, reverse power flow constraints and neutral line current constraints. Through improving the node admittance matrix and model convexity, the complexity of solving the problem is reduced. The CPLEX algorithm package was used to solve the problem. Based on a 21-bus three-phase four-wire low-voltage distribution network, a 24-h multi-period simulation was undertaken to verify the feasibility and effectiveness of the proposed scheme.

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

Sustainability ◽

10.3390/su11061774 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1774 ◽

Cited By ~ 3

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.

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Stratified Control Applied to a Three-Phase Unbalanced Low Voltage Distribution Grid in a Local Peer-to-Peer Energy Community

Energies ◽

10.3390/en14113290 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3290

Author(s):

Bharath Varsh Rao ◽

Mark Stefan ◽

Roman Schwalbe ◽

Roman Karl ◽

Friederich Kupzog ◽

...

Keyword(s):

Power Flow ◽

Optimal Power Flow ◽

Low Voltage ◽

Local Energy ◽

Voltage Distribution ◽

Distribution Grid ◽

Optimal Power ◽

Three Phase ◽

Control Scheme ◽

Energy Community

This paper presents control relationships between the low voltage distribution grid and flexibilities in a peer-to-peer local energy community using a stratified control strategy. With the increase in a diverse set of distributed energy resources and the next generation of loads such as electric storage, vehicles and heat pumps, it is paramount to maintain them optimally to guarantee grid security and supply continuity. Local energy communities are being introduced and gaining traction in recent years to drive the local production, distribution, consumption and trading of energy. The control scheme presented in this paper involves a stratified controller with grid and flexibility layers. The grid controller consists of a three-phase unbalanced optimal power flow using the holomorphic embedding load flow method wrapped around a genetic algorithm and various flexibility controllers, using three-phase unbalanced model predictive control. The control scheme generates active and reactive power set-points at points of common couplings where flexibilities are connected. The grid controller’s optimal power flow can introduce additional grid support functionalities to further increase grid stability. Flexibility controllers are recommended to actively track the obtained set-points from the grid controller, to ensure system-level optimization. Blockchain enables this control scheme by providing appropriate data exchange between the layers. This scheme is applied to a real low voltage rural grid in Austria, and the result analysis is presented.

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