A unifying energy-based approach to optimal frequency and market regulation in power grids

In this paper we provide a unifying energy-based approach to the modeling, analysis and control of power systems and markets, which is based on the port-Hamiltonian framework. Using a primal-dual gradient method applied to the social welfare problem, a distributed dynamic pricing algorithm in port-Hamiltonian form is obtained. By interconnection with the physical model a closed-loop port-Hamiltonian system is obtained, whose properties are exploited to prove asymptotic stability to the optimal points. This result is extended such that also general nodal power constraints are included into the social welfare problem. Additionally, the cases of line congestion and power transmission cost in (a)cyclic networks considering (non)linear power flow models are covered as well. Finally, we provide port-Hamiltonian descriptions and analysis of the well studied distributed averaging proportional integral (DAPI) and certain internal-model-based controllers, which solve an optimal frequency regulation problem.

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