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Strategic expansion planning for electrical networks considering uncertainties

โœ Scribed by Tobias Paulun


Publisher
John Wiley and Sons
Year
2006
Tongue
English
Weight
225 KB
Volume
16
Category
Article
ISSN
1430-144X

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โœฆ Synopsis


This article describes a newly developed method for expansion planning of electrical networks with respect to long-term cost-efficient target networks that have been calculated beforehand. Unlike existing methods, the proposed method does not calculate discrete points in time for the realization of expansion steps, but optimal if/ then-relations between expansion steps and uncertainties of network planning. The results of the expansion planning process are, therefore, optimal strategies for the future development of existing networks. Additionally, uncertainties of network planning can be considered in a more effective way by describing expansion strategies in relation to these uncertainties. Thereby, not only the computation time for solving the optimization problem has been reduced significantly but also an exponentially growing computational effort has been avoided.

The developed method is based on Ant Colony Optimization (ACO). Heuristic rules have been derived in order to improve the efficiency of the optimization approach. Since long-term cost-efficient target networks define the network structure that should be reached in the future, no explicit optimization of the network topology is necessary. Thus, different voltage levels can be optimized in one integrated approach with the developed method.

An exemplary case study presented in this article proves the functionality of the developed method.


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INVESTMENT PLANNING FOR ELECTRICITY GENE
โœ Shaligram Pokharel; K. Ponnambalam ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 198 KB

Some of the essential features of electricity generation expansion planning are discussed here. The emphasis in this paper is on the development of a methodology to analyse electricity planning problems when the variables are deterministic and stochastic in nature. Our analysis with a test problem i