Development of a novel algorithm for optimal capacitor placement in distribution systems

•The HCODEQ algorithm for solving the large-scale capacitor placement systems.•Only four parameters are needed in the HCODEQ method.•The values of used parameters in HCODEQ are easily to assign than the other EAs.•Four systems used to compare the performance of the HCODEQ, CODEQ, DE, SA, and AS.•It is observe that the HCODEQ is suitable for application to large-scale systems.

Optimal capacitor placement in distribution systems solved by the hybrid method of CODEQ (called HCODEQ method) is proposed in this work. The concepts of chaotic search, opposition-based learning, and quantum mechanics are used in the CODEQ method to overcome the drawback of parameters selection in the differential evolution (DE). However, a larger population size must be used in the CODEQ method. That is a drawback for all evolutionary algorithms (EAs). To overcome this drawback, acceleration operation and migrating operation are embedded into the CODEQ method, i.e. HCODEQ method. The use of these two operations can increase the convergence speed without decreasing the diversity among individuals. One benchmark function and various-scale capacitor placement systems are used to compare the performance of the proposed method, CODEQ method, DE, simulated annealing (SA), and ant system (AS). Numerical results show that the performance of the HCODEQ method is better than the other methods.