Title:Optimal Scheduling Method of Medium and Low Voltage AC-DC Hybrid Distribution Network Based on Edge Cloud Cooperation
Volume: 18
Author(s): Yongxiang Cai*, Hongyan He, Yueqi Wen, Yuanlong Gao, Qiming Zhang, Song Zhang and Guohao Lin
Affiliation:
- Electric Power Research Institute of Guizhou Power Grid Co. Ltd., Guiyang, 550002, China
Keywords:
AC-DC, distribution network, medium and low voltage, edge cloud cooperation, photovoltaic consumption, power quality.
Abstract:
Introduction: The rapid advancement of power electronics technology has endowed VSCinterconnected
AC/DC hybrid distribution networks with superior operational advantages, including
enhanced power supply capacity and improved compatibility with renewable energy integration. Furthermore,
the progressive development of cloud computing and edge computing architectures has significantly
developed cloud-edge collaborative control technologies. Moreover, to synergistically leverage
these dual technological advancements, this paper proposes a coordinated cloud-edge control methodology
for medium/low-voltage VSC-based AC/DC hybrid distribution systems.
Methods: This paper proposes a cloud-edge coordinated control methodology for VSC-interconnected medium/
low-voltage AC/DC hybrid distribution networks. The methodological framework comprises three principal
phases: First, a comprehensive analysis is conducted on the interaction mechanisms and regulatory capabilities
between cloud servers and edge computing nodes. Subsequently, a hierarchical control strategy is developed
through cloud-edge coordination, where the cloud layer optimizes network loss minimization while
edge layers simultaneously minimize the weighted sum of power losses and three-phase imbalance levels.
Finally, the multi-objective optimization model is systematically transformed into a second-order cone programming
(SOCP) formulation, establishing an efficient convex optimization framework.
Results: A comprehensive case study was conducted on a representative AC/DC hybrid medium/lowvoltage
distribution network topology to validate the proposed methodology. The numerical results
demonstrate that the medium-voltage (MV) side dispatch strategy achieves 52% network loss reduction
compared to pre-dispatch conditions through active-reactive power coupling-enhanced photovoltaic
accommodation. Furthermore, the cloud-edge coordinated framework enables deep exploitation of operational
potential in low-voltage (LV) AC/DC interconnected feeder sections, effectively mitigating
voltage violations while maintaining three-phase equilibrium constraints. Particularly, the synergistic
optimization mechanism reduces power losses to 48% of baseline values through coordinated control of
converter stations and intelligent edge devices.
Discussion: The results of this paper show that the proposed method can promote the photovoltaic consumption
of medium and low voltage AC / DC hybrid distribution network with high proportion of renewable
energy generation access, make full use of the advantages of DC lines in new energy access
capacity and the advantages of flexible equipment in flexible regulation and control ability, and ensure
that the voltage of distribution network does not exceed the limit and the three-phase unbalance degree
does not exceed the limit in the period of high photovoltaic output. However, it should be noted that the
method proposed in this paper has certain limitations. The method proposed in this paper has higher
requirements for global communication. For the low-voltage distribution station area with incomplete
communication and incomplete measurement, distributed control and other methods are more suitable.
Conclusion: This study addresses the challenge of insufficient photovoltaic (PV) hosting capacity
caused by large-scale distributed PV integration in medium/low-voltage distribution networks. Physically,
we develop a hybrid AC/DC distribution network topology leveraging the flexible power dispatch
capabilities of voltage source converters (VSCs), thereby overcoming the conventional radial topology
constraints. Computationally, a cloud-edge coordinated control architecture driven by distributed computing
paradigms is proposed, which synergistically exploits the regulation potential of low-voltage
(LV) feeder sections through two coordinated mechanisms: 1) A hierarchical optimization framework
that decouples system-level objectives (cloud layer) and local constraints (edge layer), significantly enhancing
computational efficiency; 2) Dynamic resource allocation that fully utilizes edge computing
nodes for real-time adjustment while maintaining global optimality through cloud-based coordination.
