Optimal planning of RDS considering PV uncertainty with different load models using artificial intelligence techniques. (25th March 2020)

• Record Type: Journal Article
• Authors: Ullah, Zia; Elkadeem, M.R.; Wang, Shaorong; Akber, Syed Muhammad Abrar
• Is Part Of: International journal of web and grid services. Volume 16:Number 1(2020)
• Page Start: 63
• Page End: 80
• Publication Date: 2020-03-25
• Subjects: radial distribution system -- photovoltaic -- distributed generators -- artificial intelligence -- distribution system planning; Web services -- Periodicals; Computational grids (Computer systems) -- Periodicals; 006.78
• Languages: English
• ISSNs: 1741-1106

Abstract

This article presents the optimised planning of RDS and proposes the artificial intelligence technique using hybrid optimisation combined with phasor particle swarm optimisation and a gravitational algorithm, called PPSO/GSA for optimal planning of RDS considering photovoltaic distributed generators in RDSs. The main objective is to maximise the RDS performance by optimally allocating the PV generators. The proposed PPSO/GSA is implemented and validated on 94-bus practical RDS located in Portuguese considering single and multiple scenarios of PV generators installation along with various loading conditions. The results reveal that the optimised planning of RDS enhance the system reliability in term of a substantial reduction in active power loss and yearly economic loss as well as improving system voltage profile. Moreover, the convergence characteristics, computational efficiency, and applicability of the proposed artificial intelligence technique are evaluated by comparative analysis and comparison with other optimisation techniques.