Integrated demand response for congestion alleviation in coupled power and transportation networks. (1st February 2021)

• Record Type: Journal Article
• Authors: Lv, Si; Wei, Zhinong; Chen, Sheng; Sun, Guoqiang; Wang, Dan
• Is Part Of: Applied energy. Volume 283(2021)
• Publication Date: 2021-02-01
• Subjects: Integrated demand response (IDR) -- Electric vehicle (EV) -- Congestion management -- Dynamic wireless charging -- Bi-level optimization; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.116206
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: The increasing prevalence of electric vehicles (EVs) and emerging dynamic wireless charging (DWC) techniques have strengthened the interdependence between transportation networks (TNs) and power distribution networks (PDNs). Under the DWC mode, EV charging demand is shifted from residential plug-in charging to charging-while-driving during commuting hours, resulting in a simultaneous congestion in coupled networks. The present study addresses this issue by developing a bi-level integrated demand response (IDR) framework for alleviating congestion in coupled networks. At the upper level, an independent system operator aims to alleviate congestion by imposing the lowest possible traffic tolls and electricity tariffs. At the lower level, rational travelers in the TN schedule their routes and departure times according to traffic tolls and traffic conditions, yielding a multi-period user equilibrium state in which the generalized travel cost of users cannot be decreased by unilaterally changing routes or departure times. Simultaneously, load aggregators in the PDN schedule flexible power demands according to electricity tariffs to minimize total energy costs. The overall bi-level programming is reformulated into a single-level mathematical program with a complementarity constraint problem, which is efficiently solved as a sequence of relaxed non-linear programming problems by a specially designed algorithm. Numerical results demonstrated the effectiveness of the proposed IDR framework in alleviating congestion and reducing total procurement costs. Highlights: A bi-level integrated demand response model for alleviating congestion in coupled transportation and power distribution networks is proposed. A multi-period user equilibrium model is proposed to capture both spatial and temporal flexibility in traffic demand. Traffic congestion is modeled explicitly to ensure realistic traffic flow distributions. An iterative relaxation algorithm is designed to solve the mathematical program with a complementarity constraint as a sequence of parameterized non-linear programming problems.