Optimal planning of RDS considering PV uncertainty with different load models using artificial intelligence techniques
by Zia Ullah; M.R. Elkadeem; Shaorong Wang; Syed Muhammad Abrar Akber
International Journal of Web and Grid Services (IJWGS), Vol. 16, No. 1, 2020

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.

Online publication date: Mon, 30-Mar-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Web and Grid Services (IJWGS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com