Litcius/Paper detail

Distributed Hierarchical Coordination of Networked Charging Stations Based on Peer-to-Peer Trading and EV Charging Flexibility Quantification

Jin Zhang, Liang Che, Xin Wan, Mohammad Shahidehpour

2021IEEE Transactions on Power Systems108 citationsDOI

Abstract

Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make full use of the EVs’ charging flexibility for improving the operational flexibility of power systems. To this end, this paper proposes a CSs-DSO distributed coordination strategy. The proposed strategy integrates a supply-curve-based quantification method to quantify the EVs’ flexibility contribution and a Nash bargaining game-theory-based peer-to-peer (P2P) transactions model for maximizing the profits of entities participating in the coordination. To tackle the CSs-DSO coordination problem that has a bi-level-parallel coupling structure, an analytical target cascading (ATC) and alternating direction method of multipliers (ADMM) jointly-based distributed solution approach is proposed. First, the CSs-DSO bi-level model is decoupled by ATC with tie-line power being the only exchanged information; then, the model is further decomposed for each CS by ADMM for protecting the CSs’ privacy and autonomy. The effect of coordination and the computational efficiency of the proposed strategy is verified by numerical simulations on a modified IEEE 33-bus distribution system connecting multiple CSs.

Topics & Concepts

Flexibility (engineering)Computer sciencePeer-to-peerDistributed computingOperator (biology)Electric power systemGame theoryPower (physics)ChemistryQuantum mechanicsMathematicsEconomicsGeneTranscription factorMicroeconomicsStatisticsRepressorBiochemistryPhysicsElectric Vehicles and InfrastructureSmart Grid Energy ManagementMicrogrid Control and Optimization