Transactive Energy for Aggregated Electric Vehicles to Reduce System Peak Load Considering Network Constraints

Abstract

Due to the increasing utilization of electric vehicles (EVs), future power grids may face challenges of system peak load that are usually solved by means of grid reinforcements. By providing flexibility, acquired from flexible consumers, such as EVs, the need for grid reinforcements can be avoided or postponed. Therefore, in order to solve the peak load problem, this paper focuses on the provision of flexibility services through the local market. It presents a framework for the participation of aggregated electric vehicles in the local market, considering the operating constraints of the grid. In the proposed framework, aggregators interact in a transactive, market-based manner, with a transactive energy (TE) operator and distribution system operator (DSO) to resolve operational problems. For the market-based operation, a bidding model is proposed and formulated as an optimization problem that minimizes the total cost of DSO for acquiring flexibility services from EVs. The proposed model uses EVs as flexible loads to illustrate the method, and it is tested with case-studies conducted on two IEEE test systems. INDEX TERMSDemand flexibility, distributed energy resources, electric vehicles, transactive energy. NOMENCLATURE A. Indices ARSALAN MASOOD received the M.S. degree from the Department of Electrical Engineering, COMSATS University Islamabad, Islamabad, Pakistan, in 2016. He is currently pursuing the Ph.D. degree with the School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China. His research interests include distributed energy resource integration with a focus on electric vehicles, DER flexibilities, and electricity markets. JUNJIE HU (Member, IEEE) received the M.Sc. degree in control theory and control engineering from Tongji University, China, in 2010, and the Ph.D. degree in electrical engineering from the Technical University of Denmark, Denmark, in 2014. He was a Postdoctoral Researcher with the Department of Electrical Engineering, Technical University of Denmark. He is currently an Associate Professor with the School of Electrical and Electronic Engineering, North China Electric Power University. His current research interests include distributed energy resources energy management, transactive energy, prosumers energy management, and multienergy system optimization.

Impact of the Charging Demand of Electric Vehicles on Distribution Grids: a Comparison Between Autonomous and Non-Autonomous Driving

“…The additional demand per lag is conservatively estimated by the maximum pairwise distance among grid nodes times the electric energy per unitary distance and is denoted E ⇤ . As detailed in the following paragraph we will use the same modelling framework as (8), where the binary variables b nv are let free. To model the requirements of autonomous driving in such a framework, we need to implement the following modeling considerations:…”

“…The work in [7] proposes a centralized scheduler based on a non-convex optimal power flow problem. The work in [8] proposes grid-aware transactive energy management for an EVs fleet.…”

A Comprehensive State-of-the-Art Review of Wired/Wireless Charging Technologies for Battery Electric Vehicles: Classification/Common Topologies/Future Research Issues

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An Optimization Model for Energy Community Costs Minimization Considering a Local Electricity Market between Prosumers and Electric Vehicles

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