Bilevel aggregator-Prosumers' optimization problem in real-time: A convex optimization approach

作     者：Shomalzadeh, Koorosh Scherpen, Jacquelien M. A. Camlibel, M. Kanat 

作者机构：Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence Faculty of Science and Engineering University of Groningen Nijenborgh 9 Groningen9747 AG Netherlands Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2021年

核心收录：

主　　题：Convex optimization 

摘      要：This paper proposes a Real-Time Market (RTM) platform for an aggregator and its corresponding prosumers to participate in the electricity wholesale market. The proposed energy market platform is modeled as a bilevel optimization problem where the aggregator and the prosumers are considered as self-interest agents. The current state-of-the-art Mathematical Programming with Equilibrium Constraints (MPEC) and Mixed-Integer Programming (MIP) based approaches to solve bilevel optimization problems are not satisfactory for real-time applications. The computation time for such approaches grows exponentially as the number of prosumers and decision variables increase. This paper presents a convex optimization problem which can capture a subset of the set of global optima of the bilevel problem as its optimal solution. Copyright © 2021, The Authors. All rights reserved.