DocumentCode :
29500
Title :
Unified electrical and thermal energy expansion planning with considering network reconfiguration
Author :
Abbasi, Ali Reza ; Seifi, Ali Reza
Author_Institution :
Sch. of Electr. & Comput. Eng., Shiraz Univ., Shiraz, Iran
Volume :
9
Issue :
6
fYear :
2015
fDate :
4 20 2015
Firstpage :
592
Lastpage :
601
Abstract :
Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio-inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed-integer non-linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines. The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems.
Keywords :
evolutionary computation; integer programming; nonlinear programming; power generation planning; thermal power stations; SFL optimisation algorithm; allocation problem; fast convergence rate; grid nodes; local minima; mixed-integer nonlinear programming problem; modified standard test systems; network reconfiguration; rapid adaptive algorithm; rewiring; robust bio-inspired evolutionary optimisation method; shuffled frog leaping optimisation algorithm; thermal energy expansion planning; thermal generation units; unified electrical energy expansion planning;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd.2014.0196
Filename :
7086364
Link To Document :
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