DocumentCode :
1655532
Title :
A review of various computational intelligence techniques for transmission network expansion planning
Author :
Dewani, B. ; Daigavane, M.B. ; Zadgaonkar, A.S.
fYear :
2012
Firstpage :
1
Lastpage :
5
Abstract :
In general, the objective of electric transmission expansion planning (TEP) is to specify addition of transmission facilities that provide adequate capacity and in the mean time maintain operating performance of electric transmission system. To achieve effective plan, exact location, capacity, timing and type of new transmission equipment must be thoroughly determined to meet demand growth, generation addition and increased power flow. However, cost-effective transmission expansion planning becomes one of the major challenges in power system optimisation due to the nature of the problem that is complex, large-scale, difficult and nonlinear. Meanwhile, mixed integer nature of TEP results in an exponentially increased number of possible solutions when system size is enlarged. This research paper deals with various planning tools for TEP based on solution methods, the treatment of the planning horizon, and the consideration of the new competitive schemes in the power sector.
Keywords :
artificial intelligence; load flow; optimisation; power apparatus; power transmission planning; TEP; computational intelligence technique; demand growth; electric transmission network expansion planning; generation addition; increased power flow; power optimisation system; transmission equipment facility; Algorithm design and analysis; Genetic algorithms; Heuristic algorithms; Optimization; Planning; Power system dynamics; dynamic transmission expansion planning (DTEP); heuristics; metaheuristics; static transmission expansion planning (STEP); transmission expansion planning (TEP);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics, Drives and Energy Systems (PEDES), 2012 IEEE International Conference on
Conference_Location :
Bengaluru
Print_ISBN :
978-1-4673-4506-4
Type :
conf
DOI :
10.1109/PEDES.2012.6484462
Filename :
6484462
Link To Document :
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