Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system

Abstract

• Introduces Chaotic Slime Mould Algorithm (CSMA) as an optimal load shedding scheme of islanded DG integrated systems. • A fitness function comprising of maximum amount of remaining load and voltage stability margin (VSM) is adopted. • IEEE 33 bus and IEEE 69 bus distribution systems are used to assess the algorithm’s efficacy. • The proposed CSMA algorithm is compared with Slime mould algorithm (SMA) and Backtrack search algorithm (BSA). In addition, non-parametric statistical analysis have been conducted to adequately compare the algorithms. • In terms of fitness value, time consumption, and convergence characteristics, CSMA outperforms both BSA and SMA. In addition, CSMA ensures a better voltage profile and provides a solution with the least amount of load to be shed. The critical challenge for an efficient islanding operation of a distribution system having Distributed Generation (DG) is preserving the frequency and voltage stability. Contemporary load shedding schemes are inefficient and do not adequately assess the optimum amount of load to shed which results in either excessive or inadequate load shedding. Hence, this paper presents an optimal load shedding technique using Chaotic Slime Mould Algorithm (CSMA) with sinusoidal map in order to achieve greater efficiency. A constrained function with static voltage stability margin (VSM) index and total remaining load after load shedding was applied to accomplish the evaluation. A total of three islanding scenarios of IEEE 33 bus and IEEE 69 bus radial distribution systems were used as test systems to assess the efficacy of the proposed load shedding approach using MATLAB software. To identify performance enhancements, the developed method was compared to Backtrack Search Algorithm (BSA) and the original SMA. According to the results, CSMA outperforms both BSA and SMA in terms of remaining load and voltage stability margin index values in all the test systems.