Optimal Power Scheduling for Smart Grids Considering Controllable Loads and High Penetration of Photovoltaic Generation

The distributed generator (DG) has a huge economical and environmental potential, especially if it is based on renewable energy sources (RESs). It is very important for the future development of smart grids. However, high penetration of DGs into distribution systems can cause voltage deviations beyo...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2014-09, Vol.5 (5), p.2350-2359
Main Authors: Ziadi, Zakaria, Taira, Shun, Oshiro, Masato, Funabashi, Toshihisa
Format: Article
Language:English
Subjects:
Battery energy storage system
controllable loads
distributed generation
distribution system
Electric utilities
Energy management
loss reduction
Optimization
photovoltaic generation
Reactive power
reactive power control
Schedules
scheduling
Smart grids
Substations
Voltage control
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Summary:The distributed generator (DG) has a huge economical and environmental potential, especially if it is based on renewable energy sources (RESs). It is very important for the future development of smart grids. However, high penetration of DGs into distribution systems can cause voltage deviations beyond the statutory range, and reverse power flow toward the substation transformer. Consequently, it can increase the distribution system losses if it is not well supervised. Thus, in order to meet smart grid objectives, DGs have to be controlled in coordination with other power resources existing in the distribution system. Controllable loads (CLs) can also help in promoting smart grids through demand response (DR) application. Therefore, this paper proposes a decision technique of an optimal reference schedule for DGs, battery energy storage system (BESS), CLs, and tap changing transformers. The main objective of the proposed optimization problem is to achieve loss reduction in the distribution system. However, other aims such as voltage control and power flow smoothing have been achieved. The optimization is performed based on predicted values of load demand and DG generation. Simulations are conducted for one operation day to illustrate the optimality of the proposed scheduling method and to assess the impact of CLs in smart grids.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2014.2323969