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• W2553595431 abstract "This paper proposes a multi-agent dynamic optimal power flow (DOPF) strategy for microgrids with distributed energy storage systems. The proposed control strategy uses a convex formulation of the ac DOPF problem developed from a d-q reference frame voltage-current model and linear power flow approximations. The convex DOPF problem is divided between autonomous agents and solved based on local information and neighbour-to-neighbour communication over a sparse communication network, using a distributed primal subgradient algorithm. Each agent is only required to solve convex quadratic sub-problems, for which robust and efficient solvers exist, making the control strategy suitable for receding horizon model predictive control. Also, the agent sub-problems require limited power network information and include only a subset of the centralised optimisation problem decision variables and constraints, providing scalability and data privacy. Unlike existing distributed optimal power flow methods, such as alternating direction method of multipliers, under the proposed control strategy the information required by each agent is independent of the communication network topology, providing increased flexibility and robustness. The performance of the proposed control strategy was verified for an ac microgrid with distributed lead-acid batteries and intermittent photovoltaic generation, using an RTDS Technologies real-time digital simulator." @default.
• W2553595431 created "2016-11-30" @default.
• W2553595431 creator A5000042067 @default.
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• W2553595431 date "2018-07-01" @default.
• W2553595431 modified "2023-09-30" @default.
• W2553595431 title "Network Topology Independent Multi-Agent Dynamic Optimal Power Flow for Microgrids With Distributed Energy Storage Systems" @default.
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• W2553595431 doi "https://doi.org/10.1109/tsg.2016.2631600" @default.
• W2553595431 hasPublicationYear "2018" @default.
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