Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i31/96004
Year: 2016, Volume: 9, Issue: 31, Pages: 1-14
Original Article
K. Prakash Kumar and B. Saravanan*
School of Electrical Engineering, [email protected]
[email protected]
*Author for correspondence
Saravanan
School of Electrical Engineering
Email:[email protected]
Objectives: Algorithms used for realtime scheduling need be simle, fast and require lesser communications with remote units. This paper introduces a two-stage algorithm for realtime scheduling in microgrids with intermittant sources. Methods/Statistical Analysis: The proposed two stage algorithm prioritizes the intemittant sources available in the microgrid based on their cost of generation in the first stage. First stage is an offline process. The second stage schedules generation among the sources in realtime using a Modified Increase-Decrease algorithm. Two modifications are proposed to the already reported Increase-Decrease algorithm to enhance optimization under two different cases of microgrid operation/ownership. Findings: The proposed algorithm is validated by using it to optimize the cost of generation in a microgrid with intermittant renewable sources in grid connected mode. The algorithm is tested under two different types of operation/ownership of the microgrid. It is found to be promising in reducing the cost of generation to a sizeable extent in both the cases of operation/ownership when compared to the already existing Increase-Decrease algorithm. After having validated its performance, the same is employed to reduce grid dependency of a microgrid with intermittant sources using a battery storage. The algorithm is found to arrive at a very optimal mix of generators and storage scheduling, ensuring lesser power drawal from the grid. Application/Improvements: Although the algorithm is used for optimization of cost of generation in this paper, it can be extended to any real time application with suitable modifications.
Keywords: Energy Storage, Grid Dependency, Intermittent Sources, Microgrid, Optimization of Generation
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