Development of Bonobo Algorithm and Its Application for Optimal Coordination of Directional Overcurrent Relays in Power Systems

Abstract

In this paper, an improved Bonobo optimization algorithm (IBO) is proposed to solve the optimal coordination of directional overcurrent relays (DOCRs) problem. This problem is important for power system protection. It is considered a nonlinear and highly constrained optimization problem. IBO aims to improve the performance of the original Bonobo optimization algorithm (BO) using Levy flight distribution and three leaders selection. Both BO and IBO are utilized to develop two solvers for optimal coordination of DOCRs. The 15-bus and 30-bus test systems are used to validate BO and IBO in minimizing the total operating time of relays with satisfying the operational constraints. The results of the proposed IBO algorithm have been compared with the original BO algorithm and other well-known algorithms. The obtained results confirmed the effectiveness and superiority of the proposed IBO algorithm compared with the other algorithms in minimizing the total operating time of relays for the optimal coordination of DOCRs. Keywords: Directional overcurrent relays; Optimal coordination; Improved Bonobo algorithm; Levy flight distribution; Three leaders selection.

Optimization Techniques for Directional Overcurrent Relay Coordination: A Comprehensive Review

“…The coordination problem of DOCRs is stated as an optimization problem that is to be minimized [110] I provide different ways for optimizing the coordination of DOCRs, depending on the specific criteria that need to be considered. One of the objective functions mentioned in Table I is presented in [3], [6], [19], [29], [33], [46], [48], [52], [69], [73], [74], [77], [78], [81], [88], [91], [93], [94], [96], [101], [102], [105]- [108], [110], [114], [117], [120], [123], [124], [128], [129], [138], [140], [142], [155]- [170], which aims to minimize the overall operating time of all relays in the system, while taking into account the CTI requirement between the backup and primary relays. However, this objective function only minimizes the operating time of the primary relay, resulting in a longer discrimination time between the primary and backup relays.…”

“…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…”

Enhancing distribution generator impact mitigation using an adaptive protection scheme based on modified pelican optimization algorithm and active database management system

“…To ensure the protection of power infrastructure from damages, the primary limiter of any protection relay is the maximum operation time (T max ), which cannot exceed 2 s. 27 Additionally, the relay settings are constrained with both maximum and minimum values for each setting, as shown in the following equations 28 :…”

“…To ensure the protection of power infrastructure from damages, the primary limiter of any protection relay is the maximum operation time ( T max ), which cannot exceed 2 s 27 . Additionally, the relay settings are constrained with both maximum and minimum values for each setting, as shown in the following equations 28 : $$${{\text{TDS}}}_{min}\le TDS\le TD{S}_{max},$$$ $$${I}_{p{\unicode{x0200A}}min}{\le }{I}_{p}{\le }{I}_{p{\unicode{x0200A}}max},$$$ $$${T}_{z2min}\le {T}_{z2}\le {T}_{z2max}.$$$…”

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.…”