Abstract
The relay coordination problem is of dire importance as it is critical to isolate the faulty portion in a timely way and thus ensure electrical network security and reliability. Meanwhile a relay protection optimization problem is highly constraint and complicated problem to be addressed. To fulfill this purpose, Harris Hawk Optimization (HHO) is adapted to solve the optimization problem for Directional Over-current Relays (DOCRs) and numerical relays. As it is inspired by the intelligent and collegial chasing and preying behavior of hawks for capturing the prey, it shows quite an impressive result for finding the global optimum values. Two decision variables; Time Dial Settings (TDS) and Plug Settings (PS) are chosen as the decision variables for minimization of overall operating time of relays. The proposed algorithm is implemented on three IEEE test systems. In comparison to other state-of-the-art nature inspired and traditional algorithms, the results demonstrate the superiority of HHO.
Highlights
IntroductionThe electrical power system is one of the most crucial systems running across the globe
The electrical power system is one of the most crucial systems running across the globe.For smooth operation of the electrical network, effective protection systems are a necessary requirement
The comparison of optimal settings determined by Harris Hawk Optimization (HHO) with seeker algorithm (SA), mixed integer non-linear programming (MINLP), analytic approach (AA), differential evolution (DE), harmony search (HS), backtracking search algorithm (BSA), modified adaptive teaching learningbased optimization algorithm (MTLBO), group search optimization (GSO), improved group search optimization (IGSO) and modified electromagnetic field optimization (MEFO) shows 5.64%, 24.77%, 1.07%, 1.89%, 8.60%, 29.19%, 78.02%, 15.50%, 4.93% and 17.31% improvements, respectively
Summary
The electrical power system is one of the most crucial systems running across the globe. Substation and DG outages in microgrids, the protection settings were determined by using the new coordination parameters set [19] All these network arrangements makes them more complex, yielding discoordination of DOCRs, that constantly leads to contingencies. The mathematical optimization techniques work on the gradient based information about the used functions for finding solutions For such type of algorithms, there is likelihood of converging to local optimum results. Energies 2021, 14, 5603 with unknown search space [46,47] To comprehend this issue, a HHO algorithm technique is examined in this work to determine the optimal DOCR parameters as compared to other state-of-the-art algorithms. The optimal settings for DOCRs were found by a novel populationbased, Nature-inspired optimization algorithm called the Harris Hawks Optimizer (HHO).
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