S. R. Samantaray

Data-Mining Model Based Intelligent Differential Microgrid Protection Scheme

This paper presents a data-mining-based intelligent differential protection scheme for the microgrid. The proposed scheme preprocesses the faulted current and voltage signals using discrete Fourier transform and estimates the most affected sensitive features at both ends of the respective feeder. Furthermore, differential features are computed from the corresponding features at both ends of the feeder and are used to build the decision tree-based data-mining model for registering the final relaying decision. The proposed scheme is extensively validated for fault situations in the standard IEC microgrid model with wide variations in operating parameters for radial and mesh topology in grid-connected and islanded modes of operation. The extensive test results indicate that the proposed intelligent differential relaying scheme can be highly reliable in providing an effective protection measure for safe and secured microgrid operation.

A New Wide-Area Backup Protection Scheme for Series-Compensated Transmission System

This paper presents a new wide-area backup protection scheme based on the phase angle of positive-sequence integrated impedance (PAPSII). The proposed scheme uses phasor measurement units (PMUs) that comply with standard C37.118.1-2011 for retrieving the phasor information. The PMUs provide the positive-sequence phasor information of the voltage and current signals at each and every bus of a system to a phasor data concentrator (PDC). The positive-sequence integrated impedance of each line of the system is extracted, and the PAPSII of each line is continuously monitored at the PDC. The values of the PAPSII help in identifying the faulted line of the power transmission system. The proposed scheme is extensively tested for different types of fault scenarios on a three-machine nine-bus power transmission network on a real-time digital simulator platform. Critical issues such as voltage inversion, current inversion, load encroachment, and the power swing are addressed in the proposed scheme. The test results indicate that the proposed scheme can overcome the limitations of existing backup protection schemes and can provide a reliable protection measure.

MOSOA-Based Multiobjective Design of Power Distribution Systems

This paper presents a multiobjective (MO) evolutionary algorithm for solving a contingency-based MO design of power distribution system (PDS) by extending the original and powerful metaheuristic approach based on a MO seeker optimization algorithm (MOSOA). Normally, reliability is a major concern in existing PDS planning, as estimation of failure rates and fault repair duration of the feeder branches is difficult in practice. The proposed planning methodology uses a contingency-load-loss index for reliability evaluation, which is independent of the failure rate and fault repair duration of the feeder branches. This planning strategy includes distribution automation devices such as automatic reclosers (RAs) to enhance the reliability and efficiency of the distribution system. The proposed algorithm generates a set of nondominated solutions by the simultaneous optimization of two conflicting objectives (economic cost and overall system reliability) using Pareto-optimality-based tradeoff analysis. The performance of the proposed approach is assessed and illustrated on a 54-bus distribution system, considering real-time design practices and meeting the additional requirements that the designer imposes. The information gained from the Pareto-optimal solution is shown to be useful for final decision making of a PDS. Furthermore, a qualitative comparison is made with the nondominated sorting genetic algorithm-II, showing the efficacy of the proposed planning approach.

High impedance fault detection in microgrid using maximal overlapping discrete wavelet transform and decision tree

The paper presents a high impedance fault (HIF) detection scheme for microgrid using maximal overlapping discrete wavelet transform (MODWT) and decision tree (DT). The small, nonlinear, random and widely varying fault current of HIF makes the over-current relay insensitive. Thus, time-frequency information is required to distinguish HIF from no-fault event. The proposed work start with retrieving the fault current which is pre-process through (decompose using) MODWT to get the details and approximation coefficient. Further, some statistical features are estimated using the details and approximation coefficient. The features extracted are used to train decision tree (DT) for accurate classification of HIF from no-fault. The proposed scheme is tested for HIFs detection in microgrid for different operating conditions. The test results show that the proposed scheme provides an effective protection measure against HIFs for safe and secured operation of microgrid.

A new cross-differential protection scheme for parallel transmission lines including UPFC

This paper proposes a new cross-differential protection scheme for a parallel transmission system in the presence of a unified power-flow controller (UPFC) in one line. A cumulative summation technique using three-phase current signals at the sending end is used for fault detection. The faulty phases are then identified by computing the spectral energies of the phasecurrents. The spectral energy of the phase currents is computed by applying a omputationally fast efficient powerful tool known as first Discrete S-Transform (FDST), suitable for analyzing power system signals. The proposed scheme has been extensively tested on different fault conditions with a wide variation in operating parameters. The test results indicate that it can accurately detect and classify the faults with clear discrimination between internal and external faults on a transmission line with a response time of a maximum one cycle from fault inception.

Simultaneous reconfiguration with DG placement using bit-shift operator based TLBO

Distributed Generations (DGs) are most commonly used in Advanced Power Distribution System (APDS) for improving the voltage level and minimizing the power loss in distribution system. This paper represents a modified Teaching Learning Based Optimization Technique (TLBO) to reconfigure the distribution system and find the optimal placement and sizing of DGs to minimize the total system loss simultaneously. In modified TLBO radial trees are consider as a initial population and possible paths between nodes are considered as design variables for finding the optimal reconfigured route. A shift operator is used to change the switch position in order to find the desired switch combination. A simultaneous reconfiguration with DG placement is done by the proposed method with different sizes of DGs in search of optimal solution. Proposed approach is illustrated on the standard IEEE-33 bus test system considering real-time design practices.

A data-mining model for protection of FACTS-based transmission line

This paper presents a data-mining model for fault-zone identification of a flexible ac transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides effective decision on fault-zone identification. Half-cycle postfault current and voltage samples from the fault inception are used as an input vector against target output “1” for the fault after TCSC/UPFC and “ -1” for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate reliable identification of the fault zone in FACTS-based transmission lines.

Location of fault on UPFC based transmission lines using sparse S-Transform

This paper presents a new fault location algorithm for a transmission line operating with a Unified Power Flow Controller (UPFC). The proposed algorithm is based on a new matrix version of the conventional S-Transform, Sparse S-Transform (SST), using selected frequency components to increase the speed of the computation significantly. A variety of faults are initiated before and after the location of UPFC on the transmission line using MATLAB/SIMULINK platform. The location of fault is estimated using SST with significant accuracies. The computational speed of the SST is almost 30 times faster than the conventional discrete S-Transform which makes it a suitable candidate for real-time application in digital relaying.

Optimal integral planning of primary-secondary distribution networks via MOEA

This paper highlights an application of a restricted population based multi-objective seeker-optimization-algorithm (MOSOA) for designing integral power distribution system (IPDS) including the grids - the primary(PG) and secondary (SG). The proposes scheme considered both the PG and SG separately along with the factors that couple both problems (PG & SG) such as sharing of the common right of way, use the same poles etc. including other factors that shows significant effect on total investment cost. The proposed planning methodology uses a contingency-load-loss index (CLLI) for reliability evaluation, does not depends on the failure rate and fault repair duration of branches. The proposed approach performance is assessed on a real case of a 75-electrical node primary-secondary residential distribution network, considering real-time design practices. The efficacy of the proposed planning model is shown by a qualitative comparison with NSGA-II.

Combined MDS–GTA and CPSO–based multi–stage planning of power distribution networks

The paper presents multistage planning of an electrical distribution networks including distributed generation (DG). Two important issues of the planning problem have been addressed. First part of this paper is focused on a modified direct search–graph theoretical approach (MDS–GTA) for feeder routing of a meshed distribution system. The second part focuses on DG placement problem in the optimal radial distribution network obtained through MDS–GTA, using constricted particle swarm optimisation (CPSO) approach. A suitable combination of the objective function and constraints are included for obtaining the minimum cost network, through MDS–GTA of meshed distribution system and to select the most suitable bus for DG placement using CPSO approach, respectively. The combined technique is extensively validated on two test distribution systems and the results obtained are highly encouraging for feeder routing and DG placement in distribution networks.