Hybridization of PSO for the Optimal Coordination of Directional Overcurrent Protection Relays

Abstract

In the electrical power system, the coordination of directional overcurrent protection relays (DOPR) plays a preeminent role in protecting the electrical power system with the help of primary and back up protection to keep the system vigorous and to avoid unnecessary interruption. The coordination between these relays should be pursued at optimal value to minimize the total operating time of all main relays. The coordination of directional overcurrent relay is a highly constrained optimization problem. The DOPR problem has been solved by using a hybridized version of particle swarm optimization (HPSO). The hybridization is achieved by introducing simulated annealing (SA) in original PSO to avoid being trapped in local optima and successfully searching for a global optimum solution. The HPSO has been successfully applied to five case studies. Furthermore, the obtained results outperform the other traditional and state of the art techniques in terms of minimizing the total operating of DOPR and convergence characteristics, and require less computational time to achieve the global optimum solution.

Optimal coordination of directional overcurrent protection relays using hybrid optimizer

“…Step 3: The obtained function is the swarm's best individual solution, and its lowest value, provided by equation (8), is the global best.…”

“…Relay coordination issues, which can be resolved via robust calculations or some evolutionary techniques, have been subject to a wide range of optimization strategies in an effort to tackle the difficult challenge at hand [5][6][7]. In certain methods, the pickup current was treated as a known variable and linear programming was used to determine the best time multiplier setting (TMS) [8,9]. Several applications of the GA and the PSO method were given, including the optimal DOPR coordination issue simulation and the grounding grids modeling [10][11][12].…”

An Improved Technique of Hybridization of PSO for the Optimal Coordination of Directional Overcurrent Protection Relays of IEEE Bus System

“…The problem of coordinating optimal DOPR protection is to minimize the sum of the operating times of all relays corresponding to the maximum fault current. The number of relays are denoted by N, and T i is the total operating time of the i-th relay [5].…”

“…Some evolutionary techniques have been used for the coordination of DOPR either in multiple networks or in ring networks. Metaheuristics evolutionary techniques include the genetic algorithm (GA) [4], particle swarm optimization (PSO) algorithm [5], firefly algorithm (FA) [6,7], whale optimization [8], Jaya algorithm (JA) [9], electromagnetic field optimization (EFO) [10], teaching learning based optimization (TLBO) algorithm [11], root tree algorithm [12], differential evolution (DE) algorithm [13,14], gray wolf optimization [15], and seeker algorithm [16]. Some computer-generated MATLAB simulated techniques include IDE (integrated development environment) [17], and NLP (Nonlinear Programming) [18], IPOPT (Interior Point Optimization) [19,20], SNOPT (Sparse Nonlinear Optimizer) [21], OPTI Tool [21], and IPM (Interior Point Method) [21], etc.…”

Optimization Techniques for Directional Overcurrent Relay Coordination: A Comprehensive Review

“…Electromagnetic Field Optimization (MEFO) [93], Rooted Tree Optimisation (RTO) [94], [95], Crow Search Algorithm (CSA) [96], Flower Pollination Algorithm (FPA) [18], [19], Gravitational Search Algorithm (GSA) [97]- [99], Water Cycle Algorithm (WCA) [100]- [105], Grey Wolf Optimizer (GWO) [14], [106]- [109], Harris Hawk Optimization (HHO) [27], [110], Group Search Optimization (GSO) [111], Imperialist Competitive Algorithm (ICA) [112], [113], Political Optimization (PO) [114], Symbiotic Organism Search Technique (SOS) [115], Whale Optimization Algorithm (WOA) [116], Sine Cosine Algorithm (SCA) [26], Discrete and Continuous Hyper-Sphere Search (DC-HSS) [2], Bonobo Algorithm (BO) [117], JAYA [6], [15], [118], and Improved Invasive Weed Optimization algorithm (IIWO) [130]. Hybrid methods, including GA-LP [131], GA-NLP [141], GA-EHA [132], PSO-LP [133], NM-PSO [135]- [137], PSO-TVAC [120], PSO-DE [121], PSO-GA [122], PSO-LSA [123], [142], PSO-SA [124], ABC-LP [125], BBO-LP [17], FA-LP…”