Capacity configuration optimisation of hybrid renewable energy system using improved grey wolf optimiser Online publication date: Mon, 06-Jun-2022
by Huili Wei; Shan Chen; Tianhong Pan; Jun Tao; Mingxing Zhu
International Journal of Computer Applications in Technology (IJCAT), Vol. 68, No. 1, 2022
Abstract: An appropriate capacity configuration of the Hybrid Renewable Energy System (HRES) contributes to reduce the equipment cost of the system configuration, and improve the operational reliability of the system. Aiming at minimising the Annualised Cost of System (ACS) and the Loss of Power Supply Probability (LPSP), a capacity configuration optimisation model of a PV-wind HRES is set up in this work. An improved Grey Wolf Optimiser (iGWO) is proposed to optimise the system's configuration. First, the Tent chaotic strategy is used to initialise the population. Then, the convergence factor is improved to balance the local and global search ability of GWO. Finally, the meteorological data of the wind speed and solar radiation in a typical year in Zhenjiang, China, are taken as a case to verify the economy and feasibility of the optimal configuration. The results show that the proposed method not only ensures the operation reliability, but also improves the economic performance of HRES.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
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 Computer Applications in Technology (IJCAT):
Login with your Inderscience username and 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