DocumentCode :
25949
Title :
Smart Distribution Grid: Optimal Day-Ahead Scheduling With Reconfigurable Topology
Author :
Golshannavaz, Sajjad ; Afsharnia, Saeed ; Aminifar, Farrokh
Author_Institution :
Sch. of Electr. & Comput. Eng., Univ. of Tehran, Tehran, Iran
Volume :
5
Issue :
5
fYear :
2014
fDate :
Sept. 2014
Firstpage :
2402
Lastpage :
2411
Abstract :
This paper proposes an optimal operational scheduling framework to be taken in use in the distribution management system (DMS) as the heart of smart active distribution networks (ADNs). The proposed algorithm targets to optimally control active elements of the network, distributed generations (DGs) and responsive loads (RLs), seeking to minimize the day-ahead total operation costs. The technical constraints of the components and the whole system are accommodated in the ac power flow fashion. As an innovative point, the DMS effectively utilizes the hourly network reconfiguration capabilities being realized by the deployment of remotely controlled switches (RCSs). Accordingly, besides the optimal schedule of active elements, the optimal topology of the network associated with each hour of the scheduling time horizon is determined as well. The effect of hourly reconfiguration on the capacity release of DGs and RLs is highlighted, which could be envisaged as a new trend in the reserve scheduling problem. Considering practical issues, the maximum daily switching actions of RCSs as well as switching costs are judicially included. The optimization procedure is formulated as a mixed-integer nonlinear problem and tackled with the genetic algorithm. To validate the satisfactory performance of the proposed framework, a 33-bus ADN is thoroughly interrogated.
Keywords :
cost reduction; distributed power generation; genetic algorithms; integer programming; load flow; nonlinear programming; power distribution economics; power generation scheduling; power system management; smart power grids; AC power flow fashion; ADN; DG; DMS; RCS; RL; day-ahead total operation cost minimization; distributed generation; distribution management system; genetic algorithm; hourly network reconfiguration capability; maximum daily switching action; mixed-integer nonlinear problem; optimal day-ahead scheduling framework; reconfigurable topology; remotely controlled switch; responsive load; smart active distribution network; smart distribution grid; Distributed power generation; Energy management; Genetic algorithms; Power system control; Reactive power; Smart grids; Active distribution network (ADN); distributed generation (DG); reconfiguration; remotely controlled switch (RCS); responsive load (RL);
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2335815
Filename :
6877724
Link To Document :
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