Credibility-based distributed frequency estimation for plug-in electric vehicles participating in load frequency control

Abstract

The accurate, robust and economic acquisition of frequency signals of plug-in electric vehicles (PEVs) is a vital prerequisite to regulate the frequency of power systems with the participation of a large number of PEVs. While the communication links among PEVs are vulnerable to cyber attacks, we propose a credibility-based distributed frequency estimation scheme to detect and isolate compromised PEVs participating in the frequency regulation. In this scheme, each PEV can distinguish its neighbors’ misbehavior based on the distributed frequency estimation and/or frequency measurements taken only at distribution substations. Then, a distributed load frequency control (DLFC) strategy is designed to integrate the credibility-based resilient distributed frequency estimation scheme. Tests under a variety of communication topologies are conducted to verify the proposed credibility-based distributed frequency estimation scheme. Simulation results of a four-area power system validate the proposed DLFC strategy after detecting and isolating the compromised PEVs can regulate the frequency quickly when suffering load variations.