Reconfiguration of MV Distribution Networks With Multicost and Multipoint Alternative Supply, Part II: Reconfiguration Plan

This is the second part of a two-paper set that presents a methodology to determine an optimal radial reconfiguration plan for a medium voltage (MV) distribution network. It is applicable to primary distribution systems with multicost and multipoint alternative supply for short and medium terms. The...

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Bibliographic Details
Published in:IEEE transactions on power systems 2008-08, Vol.23 (3), p.1401-1407
Main Authors: Fajardo, O.F., Vargas, A.
Format: Article
Language:English
Subjects:
Ac power flow
Cost function
Costs
Demand
Distributed control
Distributed power generation
Dynamic programming
economic dispatch
energy price
Environmental economics
Fuel economy
loss
Marketing
Medium voltage
Methodology
minimization costs
network reconfiguration
Network topology
Networks
Optimization
Power generation
Power generation economics
radialization
Reconfiguration
Studies
Switching theory
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Summary:This is the second part of a two-paper set that presents a methodology to determine an optimal radial reconfiguration plan for a medium voltage (MV) distribution network. It is applicable to primary distribution systems with multicost and multipoint alternative supply for short and medium terms. The optimization criterion is based on minimizing the operation costs, including the purchased energy cost and switching cost. In addition to the proposed methodology, a main contribution of the work is to evaluate the impact of the energy price on the operative topology working within a competitive market structure, where the demand is supplied from several purchase nodes featuring significantly different energy prices. The methodology is based on dynamic programming, heuristics, and a method to calculate the economic dispatch (ED) through radialization specifically designed for multicost and multipoint alternative supply, as is the case of distribution networks. The capacity of the network components, the service quality, and the dynamics of the demand are considered. Finally, the advantages of applying the methodology to a realistic distribution network are discussed.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2008.926702