A Distributed Economic Model Predictive Control Design for a Transactive Energy Market Platform in Lebanon, NH

Abstract: The electricity distribution system is fundamentally changing due to the widespread adoption of variable renewable energy resources (VREs), network-enabled digital physical devices, and active consumer engagement. VREs are uncertain and intermittent in nature and pose various technical challenges to power systems control and operations thus limiting their penetration. Engaging the demand-side with control structures that leverage the benefits of integral social and retail market engagement from individual electricity consumers through active community-level coordination serves as a control lever that could support the greater adoption of VREs. This paper presents a Distributed Economic Model Predictive control (DEMPC) algorithm for the electric power distribution system using the augmented lagrangian alternating direction inexact newton (ALADIN) algorithm. Specifically, this DEMPC solves the Alternating Current Optimal Power Flow (ACOPF) problem over a receding time-horizon. In addition, it employs a social welfare maximization of the ACOPF to capture consumer preferences through explicit use of time-varying utility functions. The DEMPC formulation of the ACOPF applied in this work is novel as it addresses the inherent dynamic characteristics of the grid and scales with the explosion of actively controlled devices on the demand-side. The paper demonstrates the simulation methodology on a 13-node Lebanon NH distribution feeder.