Comparative Analysis of Optimal Power Flow Algorithms in Networks with Distributed Generation
DOI:
https://doi.org/10.31861/sisiot2026.1.01009Keywords:
optimal power flow, distributed energy resources, distributed optimisation, distribution networks, closed-loop controlAbstract
This paper presents the formulation of the optimisation problem and a comparative analysis of real-time optimal power flow (RT-OPF) algorithms for distribution networks with a high penetration of distributed energy resources (DERs), including solar and wind generation as well as battery energy storage systems. The intermittent nature of many DERs and the emergence of bidirectional power flows increase the risk of violations of operational constraints, primarily voltage deviations and overloading of network elements. This creates a need for fast DER coordination mechanisms capable of operating on a sub-second timescale under limited communication bandwidth. The RT-OPF problem is formulated as a constrained optimisation problem in which the active and reactive power setpoints of DERs are selected to minimise aggregate undesirable effects and operating costs, subject to compliance with the local technical constraints of the devices and the network operating limits. Three algorithmic approaches widely described in the literature are considered: the primal-dual gradient method (PDGM), the alternating direction method of multipliers (ADMM), and proximal atomic coordination (PAC). The comparison is carried out according to five practically important criteria: the number of iterations per control interval, the complexity of local computations, communication requirements and scalability, robustness to delays and partial asynchronicity, and the ability to ensure compliance with local and network constraints in closed-loop control. It is shown that PDGM is generally the most suitable baseline choice for sub-second RT-OPF in large-scale aggregator-based systems owing to the simplicity of its local updates and its compact data exchange, whereas PAC provides smoother behaviour near active constraints at the cost of a more computationally demanding local step. ADMM can achieve high consensus accuracy given sufficient iterations; however, in practice it is more appropriate for slower control loops and in the presence of a reliable synchronous communication infrastructure.
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