An Effective Algorithm for MAED Problems with a New Reliability Model at the Microgrid

被引:7
|
作者
Naderipour, Amirreza [1 ]
Kalam, Akhtar [2 ]
Abdul-Malek, Zulkurnain [1 ]
Davoudkhani, Iraj Faraji [3 ]
Bin Mustafa, Mohd Wazir [4 ]
Guerrero, Josep M. [5 ]
机构
[1] Univ Teknol Malaysia, Fac Engn, Sch Elect Engn, Inst High Voltage & High Current, Johor Baharu 81310, Malaysia
[2] Victoria Univ, Coll Engn & Sci, Melbourne, Vic 3047, Australia
[3] Islamic Azad Univ, Khalkhal Branch, Dept Elect Engn, Khalkhal 3136756817, Iran
[4] Univ Teknol Malaysia, Sch Elect Engn, Johor Baharu 81310, Malaysia
[5] Aalborg Univ, Villum Ctr Res Microgrids CROM, Dept Energy Technol, DK-9220 Aalborg, Denmark
关键词
microgrid; multi-area economic dispatch (MAED); phasor particle swarm optimization (PPSO); reliability-based MAED; reserve constraints; total pollutant emissions;
D O I
10.3390/electronics10030257
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a new framework for multi-area economic dispatch (MAED) in which the cost associated with the reliability consideration is taken into account together with the common operational and emission costs using expected energy not supplied (EENS) index. To improve the reliability level, the spinning reserve capacity is considered in the model as well. Furthermore, the MAED optimization problem and non-smooth cost functions are taken into account as well as other technical limitations such as tie-line capacity restriction, ramp rate limits, and prohibited operating zones at the microgrid. Considering all the above practical issues increases the complexity in terms of optimization, which, in turn, necessitates the use of a powerful optimization tool. A new successful algorithm inspired by phasor theory in mathematics, called phasor particle swarm optimization (PPSO), is used in this paper to address this problem. In PPSO, the particles' update rules are driven by phase angles to essentially ensure a spread of variants across the population so that exploitation and exploration can be balanced. The optimal results obtained via simulations confirmed the capability of the proposed PPSO algorithm to find suitable optimal solutions for the proposed model.
引用
收藏
页码:1 / 23
页数:22
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