Application of a Continuous Particle Swarm Optimization (CPSO) for the Optimal Coordination of Overcurrent Relays Considering a Penalty Method

Abstract

Abstract:In an electrical power system, the coordination of the overcurrent relays plays an important role in protecting the electrical system by providing primary as well as backup protection. To reduce power outages, the coordination between these relays should be kept at the optimum value to minimize the total operating time and ensure that the least damage occurs under fault conditions. It is also imperative to ensure that the relay setting does not create an unintentional operation and consecutive sympathy trips. In a power system protection coordination problem, the objective function to be optimized is the sum of the total operating time of all main relays. In this paper, the coordination of overcurrent relays in a ring fed distribution system is formulated as an optimization problem. Coordination is performed using proposed continuous particle swarm optimization. In order to enhance and improve the quality of this solution a local search algorithm (LSA) is implanted into the original particle swarm algorithm (PSO) and, in addition to the constraints, these are amalgamated into the fitness function via the penalty method. The results achieved from the continuous particle swarm optimization algorithm (CPSO) are compared with other evolutionary optimization algorithms (EA) and this comparison showed that the proposed scheme is competent in dealing with the relevant problems. From further analyzing the obtained results, it was found that the continuous particle swarm approach provides the most globally optimum solution.

Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems

“…In [30,31], several bio-inspired algorithms were developed to solve the DOCR coordination issue by designing a linear formulation. In [32][33][34][35][36], a different version of particle swarm optimization (PSO) was used to determine the optimum values for DOCRs. A different version of the differential algorithm was reported in [37] to solve the DOCR coordination problem to point out the superiority of modified differential evolution algorithms.…”

An Effective Coordination Setting for Directional Overcurrent Relays Using Modified Harris Hawk Optimization

“…Various algorithms have been used to solve the DOCR coordination problem like the genetic algorithm [16], teaching-learning based algorithm [17], improved firefly algorithm [18], gray wolf optimizer [19], modified particle swarm optimizer [20], continuous particle swarm optimizer [21], nature-inspired whale optimization [22], new-rooted tree algorithm [23], an adaptive modified firefly algorithm [24], PESA-II [25], new time-currentvoltage characteristics by constrained linear programming [26], gravitational search algorithm [27], hyper spherical search algorithm [28], MILP approach [29], high performance hybrid algorithm [30], cuckoo linear algorithm [31], an enhanced backtracking search algorithm [32], a modified real-coded genetic algorithm [33], an ant-lion optimization [34], modified water-cycle algorithm [35], imperialistic competition algorithm [36], sine-cosine algorithm [37], an enhanced grey wolf optimizer [38], bonobo algorithm [39], political optimization algorithm [40] and many more.…”

An Optimized Adaptive Protection Scheme for Numerical and Directional Overcurrent Relay Coordination Using Harris Hawk Optimization

“…In [26,27] a few bio-motivated algorithms were developed to tackle the DOCR coordination issue by designing a linear formulation. In [28][29][30][31][32], a different version of particle swarm optimization (PSO) was used to determine the optimum values for DOCRs. A different version of the differential algorithm was reported in [33] to solve the DOCR coordination problem to point out the superiority of modified differential evolution algorithms.…”