Incentivizing Truth-Telling in MPC-based Load Frequency Control

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 fully addressed in the literature on online mechanism design. We propose a class of real-time monetary compensation schemes that incentivize market participants to report their private parameters truthfully at every time step, which enables the system operator to implement MPC-based LFC in a socially optimal manner.