Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Vosoogh, Mahdi | Kamyar, Mohsen | Akbari, Ayat | abbasi, Alireza
Affiliations: Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran
Note: [] Corresponding author. Alireza abbasi, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran. E-mail: a.ab.gol61@gmail.com
Abstract: The consumer's demand of more reliable and economic sources has made an impact on the new competitive electricity markets. In this regard, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach. This paper presents a novel solution methodology based on Teacher-Learning-Based Optimization (TLBO) algorithm to solve the optimal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), photovoltaic (PV) and Micro Turbine (MT). Moreover, storage devices have been considered to meet the energy mismatch. The solution of this nonlinear constraint optimization problem minimizes the total cost of the grid and RESs, concurrently. Nevertheless, in finding the optimal solution, the interactive effects of MG and utility in a 24 hour time interval are taken into consideration which would increase the complexity of the problem intensely. In order to explore the total search space globally, a modification method is proposed which is compromised of two modification methods based on TLBO. In the end, the suggested algorithm is tested through a typical renewable MG as the test system to demonstrate the superiority of the proposed method over the other well-known algorithms.
Keywords: Renewable micro-grid (MG), renewable power sources (RESs), modified teacher-learning-based optimization (MTLBO), nonlinear constraint optimization
DOI: 10.3233/IFS-131014
Journal: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 1, pp. 465-473, 2014
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl