Incentivizing Truth-Telling in MPC-based Load Frequency Control
Takashi Tanaka, Vijay Gupta

TL;DR
This paper introduces a real-time monetary mechanism that incentivizes truthful reporting of private information by power generators, enabling socially optimal model predictive control for load frequency regulation despite strategic behavior.
Contribution
It proposes a novel dynamic mechanism design framework that ensures truthful reporting in MPC-based load frequency control with self-interested generators.
Findings
Mechanism guarantees truthful reporting at each time step.
Ensures socially optimal load frequency control implementation.
Addresses dynamic strategic interactions in online settings.
Abstract
We present a mechanism for socially efficient implementation of model predictive control (MPC) algorithms for load frequency control (LFC) in the presence of self-interested power generators. Specifically, we consider a situation in which the system operator seeks to implement an MPC-based LFC for aggregated social cost minimization, but necessary information such as individual generators' cost functions is privately owned. Without appropriate monetary compensation mechanisms that incentivize truth-telling, self-interested market participants may be inclined to misreport their private parameters in an effort to maximize their own profits, which may result in a loss of social welfare. The main challenge in our framework arises from the fact that every participant's strategy at any time affects the future state of other participants; the consequences of such dynamic coupling has not been…
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Taxonomy
TopicsSmart Grid Energy Management · Electric Power System Optimization · Microgrid Control and Optimization
