Implementation of multi-objective seeker-optimization-algorithm for optimal planning of primary distribution systems including DSTATCOM

• Published in: International journal of electrical power & energy systems 2016-05, Vol.77, p.439-449
• Main Authors: Kumar, Deepak, Samantaray, S.R.
• Format: Article
• Language: English
• Subjects: Algorithms; Automatic reclosers (RAs); Automation; Compensation; Contingency-load-loss index (CLLI); Devices; Distribution static compensator (DSTATCOM); Electric potential; Multi-objective seeker-optimization-algorithm (MOSOA); Non-dominated sorting genetic algorithm-II (NSGA-II); Optimization; Power distribution; Voltage
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2015.11.047

•Multi-objective seeker-optimization-algorithm is developed.•Both cost and reliability trade-off analysis is carried out to obtain best solution.•Optimal placement of automatic reclosers enhancing system reliability.•Reduction in computational time and minimizes memory requirements. This paper develops an approach based on a multi-objective seeker-optimization-algorithm (MOSOA) for designing of an advanced power distribution system (PDS) including distribution static compensator (DSTATCOM). The proposed planning methodology uses a contingency-load-loss index (CLLI) for reliability evaluation, which is independent of the failure rate and fault repair duration of the feeder branches, which is difficult to obtain in practice. To enhance the reliability and operation efficiency of the conventional power distribution system, the proposed approach includes distribution automation devices such as automatic reclosers (RAs) in the planning strategy. The proposed study simultaneously obtains the optimal placement and sizing of the DSTATCOM in reactive power compensation for system voltage control to avoid the voltage violation problem. The effectiveness of the proposed algorithm is tested on a 54-bus distribution system, considering real-time design practices. The information gained from the pareto-optimal solution is shown to be useful for final decision making of a PDS. Furthermore, a qualitative comparison is made with NSGA-II, showing the efficiency of the proposed planning approach. The presented results show the accuracy and efficiency of the proposed method.