Long term scheduling for optimal allocation and sizing of DG unit considering load variations and DG type
•We presented a long-term scheduling for optimal allocation and sizing of DG unit.•We presented a general equation of generation for different loading condition.•The optimal size of DG unit has been linearly changed as load changes.•The optimal location of DG unit has been fixed at different loading...
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Veröffentlicht in: | International journal of electrical power & energy systems 2014-01, Vol.54, p.277-287 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •We presented a long-term scheduling for optimal allocation and sizing of DG unit.•We presented a general equation of generation for different loading condition.•The optimal size of DG unit has been linearly changed as load changes.•The optimal location of DG unit has been fixed at different loading condition.•The DNOs generation scheduling has been facilitated over the planning horizon.
This paper proposes a new long term scheduling for optimal allocation and sizing of different types of Distributed Generation (DG) units in the distribution networks in order to minimize power losses. The optimization process is implemented by continuously changing the load of the system in the planning time horizon. In order to make the analysis more practical, the loads are linearly changed in small steps of 1% from 50% to 150% of the actual value. In each load step, the optimal size and location for different types of DG units are evaluated. The proposed approach will help the distribution network operators (DNOs) to have a long term planning for the optimal management of DG units and reach the maximum efficiency. On the other hand, since the optimization process is implemented for the entire time period, the short term scheduling is also possible. The proposed method is applied to IEEE 33-bus test system using both the analytical approach and particle swarm optimization (PSO) algorithm. The simulation results show the effectiveness and acceptable performance of the proposed method. |
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ISSN: | 0142-0615 1879-3517 |
DOI: | 10.1016/j.ijepes.2013.07.016 |