A Comparison of Metaheuristic Techniques for Solving Optimal Sitting and Sizing Problems of Capacitor Banks to Reduce the Power Loss in Radial Distribution System

Abstract

The losses in the radial distribution system are inevitable which needs to be minimized for the proper transmission of power to the end customers. This problem can be solved by the allocation of capacitor banks at proper locations with appropriate sizing. These allocations need an efficient approach for the performance enhancement of RDS. In this paper, several metaheuristic techniques such as particle swarm optimization (PSO), Harmony search, Bat, Cuckoo, and Grey-wolf (GW) algorithms are employed to find the size of capacitor banks. Loss sensitivity analysis is considered for the indication of candidate buses where a capacitor has to be installed to reduce the total system losses and ultimately increase efficiency. Cost-effectiveness, power loss minimization, and voltage enhancement can be determined and compared for these 5 techniques and are implemented on the IEEE-34 bus system to illustrate the efficacy of each of them. The results show the advantages and drawbacks of the techniques separately. The simulations are carried out in MATLAB.

Selection and Location of Fixed-Step Capacitor Banks in Distribution Grids for Minimization of Annual Operating Costs: A Two-Stage Approach

“…On the other hand, the follower corresponds to a power flow tool that allows for determining the final objective function values. The leader-follower optimization approach allows for decoupling the discrete optimization problem from that of the nonlinear power flow, which allows for exploring and exploiting the solution space through penalty factors, with excellent numerical results as reported in [32] for five different metaheuristic optimization methods compared regarding the problem of the optimal placement and sizing of capacitor banks for distribution system applications.…”

A novel heap-based optimizer for allocation of shunt capacitors in radial distribution network

“…[26] has used the remora optimization algorithm (ROA) to address the OSASC problem in the RDN in order to reduce costs associated with losses, purchases, and installations, as well as the operating costs of capacitors under various loading circumstances. For the purpose of solving OSASC and minimizing power loss in the radial distribution network, [27] created and conducted a comparison analysis of several population-based algorithms, such as Particle Swarm Optimization, harmony search, BAT algorithm, cuckoo search, and greywolf (RDN). Depending on the goal that was taken into consideration, all of the aforementioned works have produced notable and encouraging outcomes in terms of power loss reduction and overall operation cost.…”

Extended Stochastic Coati Optimizer

“…In studies regarding manufacturing systems, metaheuristics have been implemented to optimize the coupling between integrated batch machines and direct shipping trucks [4], reducing risk in the spare part inventory system [5], and so on. In studies regarding power systems, metaheuristics have been implemented to optimize the installation and allocation of the distributed generation units [6], radial distribution system [7], reactive power flow in the large-scale power system [8], and so on.…”