Distributed Optimal Power Flow for Smart Microgrids

By Emiliano Dall'Anese, Hao Zhu, Georgios B. Giannakis. IEEE Transactions on Smart Grid, 2012

738 citations recorded by the source corpus.

Optimal power flow (OPF) is considered for microgrids, with the objective of minimizing either the power distribution losses, or, the cost of power drawn from the substation and supplied by distributed generation (DG) units, while effecting voltage regulation. The microgrid is unbalanced, due to unequal loads in each phase and non-equilateral conductor spacings on the distribution lines. Similar to OPF formulations for balanced systems, the considered OPF problem is nonconvex. Nevertheless, a semidefinite programming (SDP) relaxation technique is advocated to obtain a convex problem solvable in polynomial-time complexity. Enticingly, numerical tests demonstrate the ability of the proposed method to attain the globally optimal solution of the original nonconvex OPF. To ensure scalability with respect to the number of nodes, robustness to isolated communication outages, and data privacy and integrity, the proposed SDP is solved in a distributed fashion by resorting to the alternating direction method of multipliers. The resulting algorithm entails iterative message-passing among groups of consumers and guarantees faster convergence compared to competing alternatives.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/12a0a8cd28cd884854e0c6760ab1f98cfc8482d7

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Citations in the corpus

Fast Local Voltage Control Under Limited Reactive Power: Optimality and Stability Analysis (2015, background): “Alternating-direction method-of-multipliers (ADMM) has been advocated in [7], [8], while a subgradient iterative solver has been developed by [9].”
Optimal Reactive Power Dispatch for Voltage Regulation in Unbalanced Distribution Systems (2016, methodology): “Therefore, extending the ideas discussed so far to unbalanced three-phase systems is well motivated [9], [20].”
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network (2019, neutral): “The cooperation and competition among agents are also important modeling paradigms in various engineering systems, such as smart grids (Dall’Anese, Zhu, and Giannakis 2013), logistics (Ying and Dayong 2005; Cao et al. 2013), and distributed vehicles/robots (Corke, Peterson, and Rus 2005; Fax and…”
Optimal Tap Setting of Voltage Regulation Transformers in Unbalanced Distribution Systems (2016, methodology): “As it will be discussed in detail in Section III-C, the optimization problem in (13) can be relaxed to a convex one by dropping the rank-1 constraint [7]–[9].”
Distributed and Decentralized Voltage Control of Smart Distribution Networks: Models, Methods, and Future Research (2017, methodology): “Voltage-constrained ADMM is used in [40] and [41] as well, for the distributive solution of the SDP-relaxed OPF problem.”
Blockchains for decentralized optimization of energy resources in microgrid networks (2017, background): “Constraints on network voltage and power power ﬂows can become signiﬁcant at high DER penetrations, and decentralized models for power ﬂow in distribution systems have been explored in [24], [25], [26].”
Control Strategies for Microgrids With Distributed Energy Storage Systems: An Overview (2018, methodology): “secondary level voltage/frequency restoration [24]–[27] and tertiary level OPF [28]–[33].”
Distributed Energy Trading: The Multiple-Microgrid Case (2013, background): “As an example, the works in [16] and [18] show that semidefinite relaxation (see [19] for further details on this technique) can, in some cases, help approximate the global optimal solution with high precision.”
Convex relaxations and linear approximation for optimal power flow in multiphase radial networks (2014, methodology): “This approach is taken in [15] for solving optimal power flow problems.”
State of the Art in Research on Microgrids: A Review (2015, background): “The study in [175] considers the OPF for microgrids, with the objective of minimizing either power distribution losses or the cost of power drawn from the substation and supplied by DGs leading to voltage regulation.”
A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems (2017, methodology): “By considering its single-phase equivalent circuit, the SDP relaxation is extended in [32] and [33] to this generalized model.”
A Fully Distributed Reactive Power Optimization and Control Method for Active Distribution Networks (2014, methodology): “A distributed semi-definite programming (SDP) solver for OPF problem with a bus injection model in microgrids has been reported [18]; however, the positive semidefiniteness of a global matrix reflects the coupling of all buses in the systems, which is very hard to decompose.”
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents (2018, methodology): “, 2005), and load management in energy networks (Dall’Anese et al., 2013), etc.”