Optimal Reactive Power Dispatch Using Chaotic Bat Algorithm

Abstract

In this paper, the chaotic bat algorithm (CBA) is applied to solve the optimal reactive power dispatch (ORPD) problem taking into account small-scale, medium-scale and large-scale power systems. ORPD plays a key role in the power system operation and control. The ORPD problem is formulated as a mixed integer nonlinear programming problem, comprising both continuous and discrete control variables. The most outstanding benefit of the bat algorithm (BA) is its good convergence for optimal solutions. The BA, however, together with other metaheuristics, often gets stuck into local optima and in order to cope with this shortcoming, the use of the CBA is proposed in this paper. The CBA results from introducing the chaotic sequences into the standard BA to enhance its global search ability. The CBA is utilized to find the optimal settings of generator bus voltages, tap setting transformers and shunt reactive power sources. Three objective functions such as minimization of active power loss, total voltage deviations and voltage stability index are considered in this study. The effectiveness of the CBA technique is demonstrated for standard IEEE 14-bus, IEEE 39 New England bus, IEEE 57-bus, IEEE 118-bus and IEEE 300-bus test systems. The results yielded by the CBA are compared with other algorithms available in the literature. Simulation results reveal the effectiveness and robustness of the CBA for solving the ORPD problem. INDEX TERMS Chaotic bat algorithm, optimal reactive power dispatch, chaotic sequences.

An Improved Heap-Based Optimizer for Optimal Reactive Power Dispatch

“…The best values of the studied single objective functions obtained by different optimization algorithms are tabulated in Table 5. The IHBO presents the best capabilities for minimizing the objective function compared with HBO, GSA [25], APOPSO [39], BA, CBA_III and CBA_IV [50], CKHA [60], Seeker optimization algorithm (SOA) [62], adaptive invasive weed optimization algorithm (MICA-IWO) [63], PSO with an aging leader and challengers (ALC-PSO) [64], and stochastic ranking with differential evolution SR-DE [65]. The convergence characteristics yielded by both HBO and IHBO for single-objective functions of the ORPD problem over IEEE 57-bus are shown in Fig.…”

“…For example, of meta-heuristics that utilize chaos theory, the GSA technique [43], GWO technique [44], butterfly optimization algorithm (BOA) [45], salp swarm algorithm (SSA) [46], moth-flame optimizer (MFO) [47]. The metaheuristics based on chaos theory for solving the ORPD problem of different objective functions have been introduced in [48,49] and Chaotic Bat Algorithm (CBA) with two modified techniques CBA_III and CBA_IV [50]. On the other hand, solving multi-objective ORPD problems based on different objective functions have been presented in the literature in [51] based on Pareto evolutionary algorithm for minimizing both active power loss and total voltage deviation.…”

Design of Fractional Swarm Intelligent Computing With Entropy Evolution for Optimal Power Flow Problems

“…Arificial bee colony f 1 , stability 2020 [51] Chaotic Bat Algorithm f 1 , f 2 , stability 2020 * f 1 and f 2 are loss and deviation minimization, respectively. for finding an optimal solution.…”

Design of Fractional Particle Swarm Optimization Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problems

“…For instance, the PSO hybridized with DE, fuzzy logic, Pareto optimal set and GSA are the recently developed competitive hybrid strategies with ability to evade local trapping and premature convergence [17][18][19][20]. While, the new variant of PSO and other hybrid solution mechanisms by relating these concepts are studied in [21][22][23][24][25][26][27].…”