2 research outputs found
Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network
In current power distribution systems, one of the most challenging operation
tasks is to coordinate the network- wide distributed energy resources (DERs) to
maintain the stability of voltage magnitude of the system. This voltage control
task has been investigated actively under either distributed optimization-based
or local feedback control-based characterizations. The former architecture
requires a strongly-connected communication network among all DERs for
implementing the optimization algorithms, a scenario not yet realistic in most
of the existing distribution systems with under-deployed communication
infrastructure. The latter one, on the other hand, has been proven to suffer
from loss of network-wide op- erational optimality. In this paper, we propose a
game-theoretic characterization for semi-local voltage control with only a
locally connected communication network. We analyze the existence and
uniqueness of the generalized Nash equilibrium (GNE) for this characterization
and develop a fully distributed equilibrium-learning algorithm that relies on
only neighbor-to-neighbor information exchange. Provable convergence results
are provided along with numerical tests which corroborate the robust
convergence property of the proposed algorithm.Comment: Accepted to 2018 American Control Conference (ACC
Dynamic Power Distribution System Management With a Locally Connected Communication Network
Coordinated optimization and control of distribution-level assets can enable
a reliable and optimal integration of massive amount of distributed energy
resources (DERs) and facilitate distribution system management (DSM).
Accordingly, the objective is to coordinate the power injection at the DERs to
maintain certain quantities across the network, e.g., voltage magnitude, line
flows, or line losses, to be close to a desired profile. By and large, the
performance of the DSM algorithms has been challenged by two factors: i) the
possibly non strongly connected communication network over DERs that hinders
the coordination; ii) the dynamics of the real system caused by the DERs with
heterogeneous capabilities, time-varying operating conditions, and real-time
measurement mismatches. In this paper, we investigate the modeling and
algorithm design and analysis with the consideration of these two factors. In
particular, a game-theoretic characterization is first proposed to account for
a locally connected communication network over DERs, along with the analysis of
the existence and uniqueness of the Nash equilibrium (NE) therein. To achieve
the equilibrium in a distributed fashion, a projected-gradient-based
asynchronous DSM algorithm is then advocated. The algorithm performance,
including the convergence speed and the tracking error, is analytically
guaranteed under the dynamic setting. Extensive numerical tests on both
synthetic and realistic cases corroborate the analytical results derived.Comment: Submitted to IEEE Journal of Selected Topics in Signal Processin