DocumentCode :
17026
Title :
Optimization of Distribution Network Incorporating Distributed Generators: An Integrated Approach
Author :
Sicong Tan ; Jian-Xin Xu ; Panda, S.K.
Author_Institution :
NUS Grad. Sch. for Integrative Sci. & Eng. (NGS), Nat. Univ. of Singapore, Singapore, Singapore
Volume :
28
Issue :
3
fYear :
2013
fDate :
Aug. 2013
Firstpage :
2421
Lastpage :
2432
Abstract :
Previous studies of distributed power and network focused only on the optimization of either the microgrid load dispatch or reconfiguration power loss. Micorgrid economic load dispatch approach normally does not support distribution network. Network reconfiguration usually does not take distributed generators into consideration. Thus, it is necessary to integrate these two sub-problems together in order to benefit the whole network. In this paper, an integrated solution that takes care of both microgrid load dispatch and network reconfiguration is proposed. The stochastic nature of wind, PV and load is taken into consideration. The forecasting of the wind, PV and load data are considered. The four bio-inspired optimization schemes are adopted to solve the problem. The results obtained have shown that the four optimization techniques are all capable of solving this problem. By using the integrated approach, microgrid can be incorporated into the network more effectively. The network can adjust itself more efficiently to allow utilization of the renewable energy resources.
Keywords :
distributed power generation; distribution networks; load forecasting; optimisation; photovoltaic power systems; power generation dispatch; power generation economics; wind power plants; PV stochastic nature; bio-inspired optimization scheme; distributed generators; distributed power; distribution network optimization; integrated approach; load stochastic nature; micorgrid economic load dispatch approach; microgrid load dispatch optimization; network reconfiguration; reconfiguration power loss; renewable energy resources; wind stochastic nature; wind-PV-load data forecasting; Power distribution planning; power generation economics; reconfiguration; renewable energy;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2013.2253564
Filename :
6497085
Link To Document :
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