scholarly journals Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems

2019 ◽  
Vol 12 (1) ◽  
pp. 4 ◽  
Author(s):  
Samuel Yankson ◽  
Mahdi Ghamkhari

The automatic generation control mechanism in power generators comes into operation whenever an over-supply or under-supply of energy occurs in the power grid. It has been shown that the automatic generation control mechanism is highly vulnerable to load altering attacks. In this type of attack, the power consumption of multiple electric loads in power distribution systems is remotely altered by cyber attackers in such a way that the automatic generation control mechanism is disrupted and is hindered from performing its pivotal role. The existing literature on load altering attacks has studied implementation, detection, and location identification of these attacks. However, no prior work has ever studied design of an attack-thwarting system that can counter load altering attacks, once they are detected in the power grid. This paper addresses the above shortcoming by proposing an attack-thwarting system for countering load altering attacks. The proposed system is based on provoking real-time adjustment in power consumption of the flexible loads in response to the frequency disturbances caused by the load altering attacks. To make the adjustments in-proportion to the frequency disturbances, the proposed attack-thwarting system uses a transactive energy framework to establish a coordination between the flexible loads and the power grid operator.

The problem of automatic generation control (AGC) is a major concern in power utilities; it plays a major role of the complicated structure and dimension of the multi-area systems. Automatic Generation Control's main intention in the multi-area system is to maintain the frequency of each control area and remain the tie-line power flows within the many defined tolerance limits by modifying the Automatic Generation Control generators’ actual power outputs to accommodate the changing load requirements. Frequency control is accomplished through the primary control mechanism or the governor control mechanism. But the Area Control Error (ACE) always present in the system. The secondary controllers are surmounting this ACE to zero. The design tunes the controllers to enhance the better dynamic performance and stability of these eccentric conditions. The goal of this work is to diminish area control error, settle time, under-shoots and over-shoots of frequency divergence and net interchange tie-line error. Generally the gain values of the PID Control parameters obtain by tribulation and error technique and it need additional computation time. To reduce this obscurity of tuning of PID gains Evolutionary algorithm approach can be habituated to optimize the PID gains. Fuzzy – PID have been employed with different objective to enhance the efficient optimal solutions to the three area system. In this proposed study, GWO technique used to maximize Fuzzy-based PID controller's Proportional, Integral and Derivative gains in Three Area System.


2020 ◽  
Vol 33 (9) ◽  
pp. 106868
Author(s):  
Adetomike Adeyemi ◽  
Mingyu Yan ◽  
Mohammad Shahidehpour ◽  
Shay Bahramirad ◽  
Aleksi Paaso

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2798
Author(s):  
Soi Jeon ◽  
Dae-Hyun Choi

A high charging demand from many electric vehicles (EVs) at a fixed charging station (FCS) with a limited number of charging poles can increase the waiting time of EVs and yield an abnormal power grid condition. To resolve these challenges, this paper presents an optimization framework in which a mobile charging station (MCS) is dispatched to the overloaded FCS to reduce the number of waiting EVs while maintaining normal power grid operation. Compared to existing MCS scheduling methods that do not consider actual power distribution system operations, the proposed framework takes into account the (i) active/reactive power flow and consumption of EVs, (ii) reactive power capability of MCS, and (iii) voltage quality in power distribution systems. In coupled transportation and power distribution systems, the proposed algorithm conducts optimal operation scheduling of MCS for both road routing and charging and discharging, thereby leading to the reduction of waiting EVs within the allowable voltage range. The proposed MCS optimization algorithm was tested in IEEE 13-bus and 33-bus distribution systems coupled with 9-node and 15-node transportation systems, respectively. The test results demonstrate the effectiveness of the proposed algorithm in terms of number of waiting EVs, voltage magnitude deviation, and reactive power of the MCS.


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