Distributed fairness-guided optimization for coordinated demand response in multi-stakeholder process networks

Demand response has become an essential operating paradigm for enabling high penetration of inter-mittent, renewable energy into the power grid. To maximize a process's potential to perform demand response, it is important to not only consider that single process but also coordinate with the entire network of self-interested supplier and customer entities. In this work, we develop optimization formu-lations that enable the network-wide coordination of different processes' operating schedules such that the benefits of coordination are shared fairly amongst stakeholders. We propose methods for solving the problems in a distributed manner that allow stakeholders to retain data privacy and avoid sharing their process models with one another. Computational studies are performed to analyze the difference in costs for different formulations and the difference in computational performance for different distributed al-gorithms. The applicability of the proposed approaches to problems of practical significance is further demonstrated through a chlorine network case study.(c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

Demand response is an essential way to integrate renewable energy into the power grid. This research focuses on coordinating operating schedules of different processes to ensure fair sharing of benefits and proposes distributed solutions to protect data privacy. Computational studies and a case study demonstrate the feasibility and applicability of the proposed approaches.