System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search

被引:233
作者
Mohamed, Faisal A. [1 ]
Koivo, Heikki N. [2 ]
机构
[1] Omar Al Mukhtar Univ, Dept Elect Engn, El Bieda, Libya
[2] Aalto Univ, Dept Automat & Syst Technol, FIN-02015 Helsinki, Finland
关键词
MicroGrid; Optimization; Online management; Mesh adaptive direct search algorithm; DISTRIBUTED GENERATION; HYBRID; DESIGN;
D O I
10.1016/j.ijepes.2009.11.003
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents a generalized formulation to determine the optimal operating strategy and cost optimization scheme for a MicroGrid. Prior to the optimization of the MicroGrid itself, models for the system components are determined using real data. The proposed cost function takes into consideration the costs of the emissions. NOx, SO2, and CO2, start-up costs, as well as the operation and maintenance costs. A daily income and outgo from sold or purchased power is also added. The MicroGrid considered in this paper consists of a wind turbine, a micro turbine, a diesel generator, a photovoltaic array, a fuel cell, and a battery storage. In this work, the Mesh Adaptive Direct Search (MADS) algorithm is used to minimize the cost function of the system while constraining it to meet the customer demand and safety of the system. In comparison with previously proposed techniques, a significant reduction is obtained. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:398 / 407
页数:10
相关论文
共 29 条
[1]   Convergence of mesh adaptive direct search to second-order stationary points [J].
Abramson, Mark A. ;
Audet, Charles .
SIAM JOURNAL ON OPTIMIZATION, 2006, 17 (02) :606-619
[2]   Can microgrids make a major contribution to UK energy supply? [J].
Abu-Sharkh, S ;
Arnold, RJ ;
Kohler, J ;
Li, R ;
Markvart, T ;
Ross, JN ;
Steemers, K ;
Wilson, P ;
Yao, R .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2006, 10 (02) :78-127
[3]  
[Anonymous], 2013, Power generation, operation, and control
[4]   Mesh adaptive direct search algorithms for constrained optimization [J].
Audet, C ;
Dennis, JE .
SIAM JOURNAL ON OPTIMIZATION, 2006, 17 (01) :188-217
[5]   A pattern search filter method for nonlinear programming without derivatives [J].
Audet, C ;
Dennis, JE .
SIAM JOURNAL ON OPTIMIZATION, 2004, 14 (04) :980-1010
[6]   Online optimal management of PEM fuel cells using neural networks [J].
Azmy, AM ;
Erlich, I .
IEEE TRANSACTIONS ON POWER DELIVERY, 2005, 20 (02) :1051-1058
[7]   Efficiency and economics of proton exchange membrane (PEM) fuel cells [J].
Barbir, F ;
Gomez, T .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 1996, 21 (10) :891-901
[8]   Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II [J].
Basu, M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (02) :140-149
[9]  
Bernow S., 1990, 90SB01 TELL I
[10]  
BOOKER AJ, 1998, OPTIMAL DESIGN CONTR, P49, DOI [10.1007/978-1-4612-1780-03, DOI 10.1007/978-1-4612-1780-03]