Privacy-Preserving Optimal Dispatch for an Integrated Power Distribution and Natural Gas System in Networked Energy Hubs

Abstract

Energy hubs (EHs) are deployed to supply multi-energy demands economically in the integrated energy systems while considering physical and operational constraints of individual energy systems. This paper presents a decentral framework for the optimal dispatch of integrated power distribution and natural gas system (IDGS) in networked energy hubs. The IDGS operator (IDGSO) is charged with delivering a constrained optimal dispatch while preserving the privacy of participants’ data. First, a comprehensive optimization model is proposed in this paper using the mixed-integer second-order cone programming and sequential second-order cone (SOC) algorithms to guarantee the exactness of SOC relaxation. In this optimization process, we consider advanced control methods, such as remotely controlled switches and static var compensators, and propose two improvements including initial point setting and a special type of cutting plane to obtain a fast and feasible solution. Next, we apply Benders decomposition for decentralizing the decision-making process in accordance with the practical leader–follower relationship between IDGSO and EHOs (EH operators) and preserving private operation data of individual EHOs. Finally, we present numerical case studies, which illustrate the effectiveness of the proposed iterative model and solution algorithm for enhancing the operation of EHs.