Ant Lion Optimization Algorithm for Renewable Distributed Generations. (1st December 2016)
- Record Type:
- Journal Article
- Title:
- Ant Lion Optimization Algorithm for Renewable Distributed Generations. (1st December 2016)
- Main Title:
- Ant Lion Optimization Algorithm for Renewable Distributed Generations
- Authors:
- Ali, E.S.
Abd Elazim, S.M.
Abdelaziz, A.Y. - Abstract:
- Abstract: Renewable sources can provide a clean and smart solution to the increased demands. Thus, Photovoltaic (PV) system and Wind Turbine (WT) are considered here as sources of Distributed Generation (DG). Allocation and sizing of DG have greatly affected on the system losses. This paper aims to propose Ant Lion Optimization Algorithm (ALOA) for optimal allocation and sizing of renewable DG sources in various distribution networks. First the most candidate buses for installing DG are suggested using Loss Sensitivity Factors (LSFs). Then the proposed ALOA is employed to deduce the locations of DG and their sizing from the elected buses. The proposed algorithm is tested on 33 and 69 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight its benefits in reducing total power losses and consequently maximizing the net saving. Moreover, the results are introduced to verify the superiority of the proposed algorithm to improve the voltage profiles for various loading conditions. Also, the Wilcoxon test is applied to confirm the effectiveness of the proposed algorithm. Highlights: Optimal allocations and sizing of renewable DG is proposed via ALOA. Multi-objective function is designed to improve system performance. ALOA is applied successfully on various distribution systems and different loadings. The superiority of ALOA is verified compared with other recent algorithms. Wilcoxon test is performed to ensure theAbstract: Renewable sources can provide a clean and smart solution to the increased demands. Thus, Photovoltaic (PV) system and Wind Turbine (WT) are considered here as sources of Distributed Generation (DG). Allocation and sizing of DG have greatly affected on the system losses. This paper aims to propose Ant Lion Optimization Algorithm (ALOA) for optimal allocation and sizing of renewable DG sources in various distribution networks. First the most candidate buses for installing DG are suggested using Loss Sensitivity Factors (LSFs). Then the proposed ALOA is employed to deduce the locations of DG and their sizing from the elected buses. The proposed algorithm is tested on 33 and 69 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight its benefits in reducing total power losses and consequently maximizing the net saving. Moreover, the results are introduced to verify the superiority of the proposed algorithm to improve the voltage profiles for various loading conditions. Also, the Wilcoxon test is applied to confirm the effectiveness of the proposed algorithm. Highlights: Optimal allocations and sizing of renewable DG is proposed via ALOA. Multi-objective function is designed to improve system performance. ALOA is applied successfully on various distribution systems and different loadings. The superiority of ALOA is verified compared with other recent algorithms. Wilcoxon test is performed to ensure the effectiveness of ALOA. … (more)
- Is Part Of:
- Energy. Volume 116:Part 1(2016)
- Journal:
- Energy
- Issue:
- Volume 116:Part 1(2016)
- Issue Display:
- Volume 116, Issue 1, Part 1 (2016)
- Year:
- 2016
- Volume:
- 116
- Issue:
- 1
- Part:
- 1
- Issue Sort Value:
- 2016-0116-0001-0001
- Page Start:
- 445
- Page End:
- 458
- Publication Date:
- 2016-12-01
- Subjects:
- Distributed Generation -- Renewable sources -- Voltage profiles -- Ant Lion Optimization Algorithm -- Loss sensitivity factors -- Wilcoxon test
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2016.09.104 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 910.xml