Sampled Value Attack Detection for Busbar Differential Protection Based on a Negative Selection Immune System

Considering a variety of sampled value(SV)attacks on busbar differential protection(BDP)which poses challenges to conventional learning algorithms,an algorithm to detect SV attacks based on the immune system of negative selection is developed in this paper.The healthy SV data of BDP are defined as self-data composed of spheres of the same size,whereas the SV attack data,i.e.,the nonself data,are preserved in the nonself space covered by spherical detectors of different sizes.To avoid the confusion between busbar faults and SV attacks,a self-shape optimization algorithm is introduced,and the improved self-data are verified through a power-frequency fault-component-based differential protection criterion to avoid false negatives.Based on the difficulty of boundary coverage in traditional negative selection algorithms,a self-data-driven detector generation algorithm is proposed to enhance the detector coverage.A testbed of differential protection for a 110 kV double busbar system is then established.Typical SV attacks of BDP such as amplitude and current phase tampering,fault replays,and the disconnection of the secondary circuits of current transformers are considered,and the delays of differential relay operation caused by detection algorithms are investigated.

Propagation Delay Measurement and Compensation for Sampled Value Synchronization in a Smart Substation

Reliable sampled value(SV)synchronization is used to ensure the reliability of protective relaying in a smart substation based on IEC 61850.In this paper,an SV synchronization method based on SV propagation delay measurement and compensation is proposed.The method does not depend on an external reference clock and has higher reliability than existing ones.The core issue in the proposed method is to measure the switching delay.The following steps are undertaken in this work:First,the composition of SV propagation delay in a smart substation is analyzed.Second,a new switch with the capability of switching delay measuring and recording is presented.Third,two laboratory tests are conducted to study the measurement accuracy of the switching delay.Finally,an SV synchronization method is presented and its application is tested on a busbar protection system to demonstrate that the proposed method can achieve SV synchronization effectively.Test results show that the measurement is sufficiently accurate for the SV propagation delay compensation.The proposed method also shows that the reliability of the protective relaying in a smart substation is significantly improved.

The Dual of the Maximum Likelihood

The Maximum Likelihood method estimates the parameter values of a statistical model that maximizes the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires the formulation of a Lagrange problem. A result of this setup is that the Lagrange multipliers associated with the linear statistical model (where sample observations are regarded as a set of constraints) are equal to the vector of residuals scaled by the variance of those residuals. The novel contribution of this paper consists in deriving the dual model of the Maximum Likelihood method under normality assumptions. This model minimizes a function of the variance of the error terms subject to orthogonality conditions between the model residuals and the space of explanatory variables. An intuitive interpretation of the dual problem appeals to basic elements of information theory and an economic interpretation of Lagrange multipliers to establish that the dual maximizes the net value of the sample information. This paper presents the dual ML model for a single regression and provides a numerical example of how to obtain maximum likelihood estimates of the parameters of a linear statistical model using the dual specification.

Shared-network scheme of SMV and GOOSE in smart substation

The network structure of the smart substation in common use was introduced,and the technical problems of the shared-network of sampled measured value(SMV)and generic object oriented substation event(GOOSE)were analyzed,such as the processing ability of network device and the intelligent device,the data real-time property and the network reliability,the effects to the substation in the condition of network fault,etc.On this basis,the feasibility of the shared-network of SMV and GOOSE was discussed,the implement scheme was presented,and eventually the solution of the shared-network of SMV and GOOSE was put forward,which based on the applications of the message priority control,restricting the switch number,virtual local area network(VLAN)and GARP multicast registration protocol(GMRP)classification flow control,flow rate limiting,etc.In the test-bed,the cases of shared-network and separate-network of SMV and GOOSE were compared and analyzed,and the result was valuable for reference.

A d-axis based current differential protection scheme for an active distribution network

The emergence of distributed generators has changed the operational mode and fault characteristics of the distribu-tion network,in a way which can severely influence protection.This paper proposes a d-axis-based current differential protection scheme.The d-axis current characteristics of inverter-interfaced distributed generators and synchronous generators are analyzed.The differential protection criterion using sampling values of the d-axis current component is then constructed.Compared to conventional phase-based current differential protection,the proposed protection reduces the number of required communication channels,and is suitable for distribution networks with inverter-interfaced distributed generators with complex fault characteristics.Finally,a 10 kV active distribution network model is built in the PSCAD platform and protection prototypes are developed in RTDS.Superior sensitivity and fast speed are verified by simulation and RTDS-based tests.