DocumentCode :
53820
Title :
A Hierarchical Framework for Long-Term Power Planning Models
Author :
Tang, Linlin ; Ferris, Michael C.
Author_Institution :
Dept. of Ind. Syst. & Eng., Univ. of Wisconsin-Madison, Madison, WI, USA
Volume :
30
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
46
Lastpage :
56
Abstract :
In this paper, we formulate a long-term planning model of transmission line expansion based on balancing investment cost and reducing consumer cost. We achieve this by formulating a hierarchical framework that is sensitive to different agents operating on different timelines, the relationships of which may be competitive, cooperative or somewhere in between. The advantage of this framework is that while it captures the complexity of long-term decision making, it maintains clarity of information flow between models, agents and timelines. For our purposes, we introduce an equilibrium model that combines grid operational concerns with the short-term competitive behavior of generation firms. An iterative solution technique is proposed to provide a Nash solution where each optimization problem is solved globally. This solution is then used to inform an overarching transmission planning model that we solve using derivative-free optimization. Using a de-congested network as a benchmark, numerical results indicate a non-alignment of the objectives of planning and operational entities, whereby easing line congestion may not offer monetary benefits to the wholesale consumer.
Keywords :
decision making; optimisation; power system planning; power system simulation; power transmission lines; Nash solution; decongested network; derivative-free optimization; iterative solution technique; long-term decision making; optimization problem; overarching transmission planning model; power planning models; transmission line; Approximation methods; Biological system modeling; Complexity theory; Generators; Investment; Linear programming; Planning; Derivative-free optimization; extended mathematical programming; hierarchical framework; power transmission planning; short-term market behavior;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2328293
Filename :
6834825
Link To Document :
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