NDLI: Hybrid energy system design using greedy particle swarm and biogeography-based optimisation

Content Provider	IET Digital Library
Author	Abuelrub, Ahmad Khamees, Mohammad Ababneh, Jehad Masri, Hussein Al
Abstract	Renewable energy systems (RESs) are affordable, clean and sustainable. However, their output power is intermittent. Therefore, RESs are usually combined with an energy storage system or conventional sources to make the overall operation uninterruptable. Optimal sizing of hybrid energy system components is imperative to be financially and technically feasible. In this study, a multi-objective optimisation based on a hybrid optimisation procedure, which combines the exploitation ability of the biogeography-based optimisation (BBO) with the exploration ability of the particle swarm optimisation (PSO), is used to handle the system design. This algorithm is known as greedy particle swarm and BBO algorithm (GPSBBO). Weighted sum method is added to the GPSBBO to handle the multi-objective nature of the design problem. A case study for a hybrid wind-PV energy system design in the standalone and grid-connected configurations is presented to illustrate the proposed method. Coverage of two sets, hypervolume and diversity performance indices are used to compare results of the proposed method to non-dominated sorting genetic algorithm and the multi-objective PSO. These indices show an improved performance of the suggested method in finding the optimal system design.
Starting Page	1657
Ending Page	1667
Page Count	11
ISSN	17521416
Volume Number	14
e-ISSN	17521424
Issue Number	Issue 10, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/14/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.0858
Journal	IET Renewable Power Generation
Publisher Date	2020-03-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	BBO Algorithm Biogeography-based Optimisation Energy Storage System Evolutionary Computation Exploration Ability Genetic Algorithm GPSBBO Greedy Algorithm Greedy Particle Swarm Hybrid Energy System Component Hybrid Energy System Design Hybrid Optimisation Procedure Hybrid Power System Hybrid Wind-PV Energy System Design Multiobjective Nature Multiobjective Optimisation Multiobjective PSO Operation Uninterruptable Optimal Sizing Optimal System Design Optimisation Optimisation Technique Output Power Pareto Optimisation Particle Swarm Optimisation Photovoltaic Power System Renewable Energy System RESs Solar Power Stations
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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