Abstract
This paper presents an Enhanced Marine Predators Algorithm (EMPA) for simultaneous optimal distribution system reconfigurations (DSRs) and distributed generations (DGs) addition. The proposed EMPA recognizes the changes opportunity in environmental and climatic conditions. The EMPA handles a multi-objective model to minimize the power losses and enhance the voltage stability index (VSI) at different loading levels. The proposed EMPA is performed on IEEE 33-bus and large-scale 137-bus distribution systems (DSs) where three distinct loading conditions are beheld through light, nominal and heavy levels. For the 33-bus DS, the proposed EMPA successfully reduces the cumulative losses by 72.4% compared to 70.36% for MPA for the three-loading levels simultaneously. As a result, significant voltage improvement is achieved for heavy, nominal and light loadings to be 95.05, 97, 98.3%, respectively. For the 137-bus DS, it successfully minimizes the losses of 81.16% under small standard deviation 4.76%. Also, the 83-bus test system is considered for fair comparative between the proposed and previous techniques. The simulation outputs revealed significant improvements in the standard MPA and demonstrated the superiority and effectiveness of the proposed EMPA compared to other reported results by recent algorithms for DSRs associated with DGs integration.
Highlights
Power system experts are committed for improving the reliability of distribution networks
In this paper, an Enhanced Marine Predators Algorithm (EMPA) is presented for simultaneous distribution system reconfigurations (DSRs) and distributed generators (DGs) integration
The suggested EMPA recognizes the scope for differences in environmental and climatic conditions, which show a major change in the Marine Predators Algorithm (MPA) standard
Summary
Power system experts are committed for improving the reliability of distribution networks. Endeavors of DS operators and interested researchers have not ceased to achieve the best performance of DSs. Endeavors of DS operators and interested researchers have not ceased to achieve the best performance of DSs One such endeavor is simultaneous control of DSRs and allocation of DGs. As such, recent studies to the implementation of an effective integration strategy has been presented; for example; manta ray foraging optimization [1]; harmony search algorithm (HSA) with an objective of minimizing real power loss and improving voltage profile [29]; combined GA and branch exchange [30]; artificial bee colony optimizer based on maximization of system loadability [31]; improved spotted hyena algorithm [32], improved elitist–jaya algorithm (IEJAYA) [5], FWA [33], firefly (FF) algorithm [34], sine-cosine algorithm [35], Harris Hawks.
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